fintech-banking-fraud-transaction-jpmorgan.ipynb

{"metadata":{"colab":{"provenance":[]},"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"name":"python","version":"3.10.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":8390777,"sourceType":"datasetVersion","datasetId":4991003}],"dockerImageVersionId":30698,"isInternetEnabled":false,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport seaborn as sns\nfrom sklearn.metrics import accuracy_score,classification_report\nfrom sklearn.ensemble import IsolationForest\nfrom sklearn.neighbors import LocalOutlierFactor\nfrom sklearn.model_selection import train_test_split\nfrom datetime import datetime\nfrom sklearn.linear_model import LogisticRegression\nimport matplotlib.pyplot as plt\nfrom sklearn.model_selection import train_test_split\nimport missingno as msno\nfrom scipy import stats\nimport plotly.express as px\nimport plotly.figure_factory as ff\nfrom plotly.subplots import make_subplots\nimport plotly.graph_objs as go\n\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.model_selection import train_test_split\nfrom imblearn.combine import SMOTETomek\nfrom collections import Counter\n\nfrom sklearn.ensemble import RandomForestClassifier\nfrom lightgbm.sklearn import LGBMClassifier\nimport xgboost as xgb\nfrom sklearn.svm import SVC\nfrom sklearn.linear_model import LogisticRegression\n\nfrom sklearn.metrics import accuracy_score\nfrom sklearn.metrics import roc_auc_score\nfrom sklearn.metrics import classification_report\nfrom sklearn.metrics import roc_curve, RocCurveDisplay\n\nimport warnings\nwarnings.filterwarnings('ignore')\n","metadata":{"id":"hEsLLRdWvkC0","execution":{"iopub.status.busy":"2024-05-13T02:49:38.347727Z","iopub.execute_input":"2024-05-13T02:49:38.349026Z","iopub.status.idle":"2024-05-13T02:49:38.363045Z","shell.execute_reply.started":"2024-05-13T02:49:38.348976Z","shell.execute_reply":"2024-05-13T02:49:38.361310Z"},"trusted":true},"execution_count":660,"outputs":[]},{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:49:38.385443Z","iopub.execute_input":"2024-05-13T02:49:38.387095Z","iopub.status.idle":"2024-05-13T02:49:38.403026Z","shell.execute_reply.started":"2024-05-13T02:49:38.387035Z","shell.execute_reply":"2024-05-13T02:49:38.401696Z"},"trusted":true},"execution_count":661,"outputs":[{"name":"stdout","text":"/kaggle/input/sml-project/fraud_payment_data_JPMorgan.csv\n","output_type":"stream"}]},{"cell_type":"code","source":"finance_dataset = pd.read_csv('/kaggle/input/sml-project/fraud_payment_data_JPMorgan.csv')\nfinance_dataset = pd.DataFrame(finance_dataset)","metadata":{"id":"CgJO5KMSvtZE","execution":{"iopub.status.busy":"2024-05-13T02:49:38.429844Z","iopub.execute_input":"2024-05-13T02:49:38.430782Z","iopub.status.idle":"2024-05-13T02:49:45.803231Z","shell.execute_reply.started":"2024-05-13T02:49:38.430739Z","shell.execute_reply":"2024-05-13T02:49:45.802213Z"},"trusted":true},"execution_count":662,"outputs":[]},{"cell_type":"code","source":"finance_dataset.info()","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"kxSCK3Uyv4gt","outputId":"14e1df1c-8887-4f82-bf19-1ed771185e56","execution":{"iopub.status.busy":"2024-05-13T02:49:45.805265Z","iopub.execute_input":"2024-05-13T02:49:45.805735Z","iopub.status.idle":"2024-05-13T02:49:47.349867Z","shell.execute_reply.started":"2024-05-13T02:49:45.805691Z","shell.execute_reply":"2024-05-13T02:49:47.348391Z"},"trusted":true},"execution_count":663,"outputs":[{"name":"stdout","text":"<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 1498177 entries, 0 to 1498176\nData columns (total 13 columns):\n #   Column            Non-Null Count    Dtype  \n---  ------            --------------    -----  \n 0   Time_step         1498177 non-null  object \n 1   Transaction_Id    1498177 non-null  object \n 2   Sender_Id         1279291 non-null  object \n 3   Sender_Account    1279291 non-null  object \n 4   Sender_Country    1279291 non-null  object \n 5   Sender_Sector     1279291 non-null  float64\n 6   Sender_lob        1279291 non-null  object \n 7   Bene_Id           1282284 non-null  object \n 8   Bene_Account      1282284 non-null  object \n 9   Bene_Country      1282284 non-null  object \n 10  USD_amount        1498177 non-null  float64\n 11  Label             1498177 non-null  int64  \n 12  Transaction_Type  1498177 non-null  object \ndtypes: float64(2), int64(1), object(10)\nmemory usage: 148.6+ MB\n","output_type":"stream"}]},{"cell_type":"code","source":"finance_dataset.shape","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"dEIynHRQv8dk","outputId":"255f4b04-71a7-4a3e-9236-78775d99836d","execution":{"iopub.status.busy":"2024-05-13T02:49:47.351430Z","iopub.execute_input":"2024-05-13T02:49:47.351806Z","iopub.status.idle":"2024-05-13T02:49:47.364564Z","shell.execute_reply.started":"2024-05-13T02:49:47.351775Z","shell.execute_reply":"2024-05-13T02:49:47.362952Z"},"trusted":true},"execution_count":664,"outputs":[{"execution_count":664,"output_type":"execute_result","data":{"text/plain":"(1498177, 13)"},"metadata":{}}]},{"cell_type":"code","source":"plt.figure(figsize = (15, 8))\nmsno.bar(finance_dataset, figsize = (15,5), sort = 'ascending', color = \"#896F82\")\nplt.show()","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":494},"id":"z2FP474SwKPQ","outputId":"a3af2073-0d52-4f83-ba62-ce98d8cdb2a9","execution":{"iopub.status.busy":"2024-05-13T02:49:47.367810Z","iopub.execute_input":"2024-05-13T02:49:47.368272Z","iopub.status.idle":"2024-05-13T02:49:52.164635Z","shell.execute_reply.started":"2024-05-13T02:49:47.368236Z","shell.execute_reply":"2024-05-13T02:49:52.163195Z"},"trusted":true},"execution_count":665,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1500x500 with 3 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"},"metadata":{}}]},{"cell_type":"code","source":"finance_dataset.head()","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":399},"id":"YfdCuuziwkEa","outputId":"b0fe5c31-cdc6-46b5-d38f-d3ce746ab113","execution":{"iopub.status.busy":"2024-05-13T02:49:52.167016Z","iopub.execute_input":"2024-05-13T02:49:52.167436Z","iopub.status.idle":"2024-05-13T02:49:52.193298Z","shell.execute_reply.started":"2024-05-13T02:49:52.167402Z","shell.execute_reply":"2024-05-13T02:49:52.191177Z"},"trusted":true},"execution_count":666,"outputs":[{"execution_count":666,"output_type":"execute_result","data":{"text/plain":"             Time_step       Transaction_Id          Sender_Id Sender_Account  \\\n0  2022-03-15 10:24:00       EXCHANGE-10115  JPMC-CLIENT-10098  ACCOUNT-10108   \n1  2022-03-15 10:24:00  QUICK-PAYMENT-10116  JPMC-CLIENT-10098  ACCOUNT-10109   \n2  2022-03-15 10:24:00    DEPOSIT-CASH-9833                NaN            NaN   \n3  2022-03-15 10:24:00       PAY-CHECK-9832   JPMC-CLIENT-9812   ACCOUNT-9825   \n4  2022-03-15 10:24:00   DEPOSIT-CHECK-9806                NaN            NaN   \n\n  Sender_Country  Sender_Sector Sender_lob           Bene_Id   Bene_Account  \\\n0            USA        35537.0        CCB               NaN            NaN   \n1            USA        15287.0        CCB      CLIENT-10100  ACCOUNT-10106   \n2            NaN            NaN        NaN  JPMC-CLIENT-9812   ACCOUNT-9826   \n3            USA        38145.0        CCB  JPMC-CLIENT-9814   ACCOUNT-9824   \n4            NaN            NaN        NaN  JPMC-CLIENT-9789   ACCOUNT-9800   \n\n  Bene_Country  USD_amount  Label Transaction_Type  \n0          NaN      558.43      0       WITHDRAWAL  \n1       CANADA      622.78      0    QUICK-PAYMENT  \n2          USA      802.54      0     DEPOSIT-CASH  \n3          USA      989.09      0        PAY-CHECK  \n4          USA      786.78      0    DEPOSIT-CHECK  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Time_step</th>\n      <th>Transaction_Id</th>\n      <th>Sender_Id</th>\n      <th>Sender_Account</th>\n      <th>Sender_Country</th>\n      <th>Sender_Sector</th>\n      <th>Sender_lob</th>\n      <th>Bene_Id</th>\n      <th>Bene_Account</th>\n      <th>Bene_Country</th>\n      <th>USD_amount</th>\n      <th>Label</th>\n      <th>Transaction_Type</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2022-03-15 10:24:00</td>\n      <td>EXCHANGE-10115</td>\n      <td>JPMC-CLIENT-10098</td>\n      <td>ACCOUNT-10108</td>\n      <td>USA</td>\n      <td>35537.0</td>\n      <td>CCB</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>558.43</td>\n      <td>0</td>\n      <td>WITHDRAWAL</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2022-03-15 10:24:00</td>\n      <td>QUICK-PAYMENT-10116</td>\n      <td>JPMC-CLIENT-10098</td>\n      <td>ACCOUNT-10109</td>\n      <td>USA</td>\n      <td>15287.0</td>\n      <td>CCB</td>\n      <td>CLIENT-10100</td>\n      <td>ACCOUNT-10106</td>\n      <td>CANADA</td>\n      <td>622.78</td>\n      <td>0</td>\n      <td>QUICK-PAYMENT</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2022-03-15 10:24:00</td>\n      <td>DEPOSIT-CASH-9833</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>JPMC-CLIENT-9812</td>\n      <td>ACCOUNT-9826</td>\n      <td>USA</td>\n      <td>802.54</td>\n      <td>0</td>\n      <td>DEPOSIT-CASH</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2022-03-15 10:24:00</td>\n      <td>PAY-CHECK-9832</td>\n      <td>JPMC-CLIENT-9812</td>\n      <td>ACCOUNT-9825</td>\n      <td>USA</td>\n      <td>38145.0</td>\n      <td>CCB</td>\n      <td>JPMC-CLIENT-9814</td>\n      <td>ACCOUNT-9824</td>\n      <td>USA</td>\n      <td>989.09</td>\n      <td>0</td>\n      <td>PAY-CHECK</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2022-03-15 10:24:00</td>\n      <td>DEPOSIT-CHECK-9806</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>JPMC-CLIENT-9789</td>\n      <td>ACCOUNT-9800</td>\n      <td>USA</td>\n      <td>786.78</td>\n      <td>0</td>\n      <td>DEPOSIT-CHECK</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"# Check Duplicates if any \nprint(\"Number of Duplicates : \", finance_dataset.duplicated().sum())","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"GMmFQnwvw1mt","outputId":"a725a428-846d-4539-f898-d3ba96754b62","execution":{"iopub.status.busy":"2024-05-13T02:49:52.197627Z","iopub.execute_input":"2024-05-13T02:49:52.198134Z","iopub.status.idle":"2024-05-13T02:49:55.514749Z","shell.execute_reply.started":"2024-05-13T02:49:52.198070Z","shell.execute_reply":"2024-05-13T02:49:55.513510Z"},"trusted":true},"execution_count":667,"outputs":[{"name":"stdout","text":"Number of Duplicates :  0\n","output_type":"stream"}]},{"cell_type":"code","source":"finance_dataset.columns","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"TNMCZM3uxG6t","outputId":"75ce6ccd-73f0-49fa-f336-124b5e82a5f9","execution":{"iopub.status.busy":"2024-05-13T02:49:55.516149Z","iopub.execute_input":"2024-05-13T02:49:55.516487Z","iopub.status.idle":"2024-05-13T02:49:55.524198Z","shell.execute_reply.started":"2024-05-13T02:49:55.516456Z","shell.execute_reply":"2024-05-13T02:49:55.522990Z"},"trusted":true},"execution_count":668,"outputs":[{"execution_count":668,"output_type":"execute_result","data":{"text/plain":"Index(['Time_step', 'Transaction_Id', 'Sender_Id', 'Sender_Account',\n       'Sender_Country', 'Sender_Sector', 'Sender_lob', 'Bene_Id',\n       'Bene_Account', 'Bene_Country', 'USD_amount', 'Label',\n       'Transaction_Type'],\n      dtype='object')"},"metadata":{}}]},{"cell_type":"code","source":"finance_dataset = finance_dataset.drop(columns = ['Time_step','Transaction_Id'],axis = 'columns')","metadata":{"id":"IMInuPYxxTjQ","execution":{"iopub.status.busy":"2024-05-13T02:49:55.525982Z","iopub.execute_input":"2024-05-13T02:49:55.526362Z","iopub.status.idle":"2024-05-13T02:49:55.652772Z","shell.execute_reply.started":"2024-05-13T02:49:55.526332Z","shell.execute_reply":"2024-05-13T02:49:55.651200Z"},"trusted":true},"execution_count":669,"outputs":[]},{"cell_type":"code","source":"finance_dataset.head()","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":399},"id":"2ErJptz2zKK-","outputId":"abc15777-47d1-4ff4-8095-ff721110bb70","execution":{"iopub.status.busy":"2024-05-13T02:49:55.654534Z","iopub.execute_input":"2024-05-13T02:49:55.654916Z","iopub.status.idle":"2024-05-13T02:49:55.676654Z","shell.execute_reply.started":"2024-05-13T02:49:55.654883Z","shell.execute_reply":"2024-05-13T02:49:55.674928Z"},"trusted":true},"execution_count":670,"outputs":[{"execution_count":670,"output_type":"execute_result","data":{"text/plain":"           Sender_Id Sender_Account Sender_Country  Sender_Sector Sender_lob  \\\n0  JPMC-CLIENT-10098  ACCOUNT-10108            USA        35537.0        CCB   \n1  JPMC-CLIENT-10098  ACCOUNT-10109            USA        15287.0        CCB   \n2                NaN            NaN            NaN            NaN        NaN   \n3   JPMC-CLIENT-9812   ACCOUNT-9825            USA        38145.0        CCB   \n4                NaN            NaN            NaN            NaN        NaN   \n\n            Bene_Id   Bene_Account Bene_Country  USD_amount  Label  \\\n0               NaN            NaN          NaN      558.43      0   \n1      CLIENT-10100  ACCOUNT-10106       CANADA      622.78      0   \n2  JPMC-CLIENT-9812   ACCOUNT-9826          USA      802.54      0   \n3  JPMC-CLIENT-9814   ACCOUNT-9824          USA      989.09      0   \n4  JPMC-CLIENT-9789   ACCOUNT-9800          USA      786.78      0   \n\n  Transaction_Type  \n0       WITHDRAWAL  \n1    QUICK-PAYMENT  \n2     DEPOSIT-CASH  \n3        PAY-CHECK  \n4    DEPOSIT-CHECK  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Sender_Id</th>\n      <th>Sender_Account</th>\n      <th>Sender_Country</th>\n      <th>Sender_Sector</th>\n      <th>Sender_lob</th>\n      <th>Bene_Id</th>\n      <th>Bene_Account</th>\n      <th>Bene_Country</th>\n      <th>USD_amount</th>\n      <th>Label</th>\n      <th>Transaction_Type</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>JPMC-CLIENT-10098</td>\n      <td>ACCOUNT-10108</td>\n      <td>USA</td>\n      <td>35537.0</td>\n      <td>CCB</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>558.43</td>\n      <td>0</td>\n      <td>WITHDRAWAL</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>JPMC-CLIENT-10098</td>\n      <td>ACCOUNT-10109</td>\n      <td>USA</td>\n      <td>15287.0</td>\n      <td>CCB</td>\n      <td>CLIENT-10100</td>\n      <td>ACCOUNT-10106</td>\n      <td>CANADA</td>\n      <td>622.78</td>\n      <td>0</td>\n      <td>QUICK-PAYMENT</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>JPMC-CLIENT-9812</td>\n      <td>ACCOUNT-9826</td>\n      <td>USA</td>\n      <td>802.54</td>\n      <td>0</td>\n      <td>DEPOSIT-CASH</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>JPMC-CLIENT-9812</td>\n      <td>ACCOUNT-9825</td>\n      <td>USA</td>\n      <td>38145.0</td>\n      <td>CCB</td>\n      <td>JPMC-CLIENT-9814</td>\n      <td>ACCOUNT-9824</td>\n      <td>USA</td>\n      <td>989.09</td>\n      <td>0</td>\n      <td>PAY-CHECK</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>JPMC-CLIENT-9789</td>\n      <td>ACCOUNT-9800</td>\n      <td>USA</td>\n      <td>786.78</td>\n      <td>0</td>\n      <td>DEPOSIT-CHECK</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"cols = finance_dataset.columns.tolist()\nnew_position = 2\n\ncols.insert(new_position, cols.pop(cols.index('Bene_Account')))\nfinance_dataset = finance_dataset[cols]\n\ncols = finance_dataset.columns.tolist()\nnew_position = 1\n\ncols.insert(new_position, cols.pop(cols.index('Bene_Id')))\nfinance_dataset = finance_dataset[cols]","metadata":{"id":"9bpvh-ykzyoZ","execution":{"iopub.status.busy":"2024-05-13T02:49:55.682601Z","iopub.execute_input":"2024-05-13T02:49:55.683020Z","iopub.status.idle":"2024-05-13T02:49:56.035776Z","shell.execute_reply.started":"2024-05-13T02:49:55.682988Z","shell.execute_reply":"2024-05-13T02:49:56.034201Z"},"trusted":true},"execution_count":671,"outputs":[]},{"cell_type":"code","source":"finance_dataset.head()","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":399},"id":"DR7OnB7b0MEn","outputId":"85562396-42ef-4672-823e-cac693715aca","execution":{"iopub.status.busy":"2024-05-13T02:49:56.038094Z","iopub.execute_input":"2024-05-13T02:49:56.038617Z","iopub.status.idle":"2024-05-13T02:49:56.063310Z","shell.execute_reply.started":"2024-05-13T02:49:56.038571Z","shell.execute_reply":"2024-05-13T02:49:56.061705Z"},"trusted":true},"execution_count":672,"outputs":[{"execution_count":672,"output_type":"execute_result","data":{"text/plain":"           Sender_Id           Bene_Id Sender_Account   Bene_Account  \\\n0  JPMC-CLIENT-10098               NaN  ACCOUNT-10108            NaN   \n1  JPMC-CLIENT-10098      CLIENT-10100  ACCOUNT-10109  ACCOUNT-10106   \n2                NaN  JPMC-CLIENT-9812            NaN   ACCOUNT-9826   \n3   JPMC-CLIENT-9812  JPMC-CLIENT-9814   ACCOUNT-9825   ACCOUNT-9824   \n4                NaN  JPMC-CLIENT-9789            NaN   ACCOUNT-9800   \n\n  Sender_Country  Sender_Sector Sender_lob Bene_Country  USD_amount  Label  \\\n0            USA        35537.0        CCB          NaN      558.43      0   \n1            USA        15287.0        CCB       CANADA      622.78      0   \n2            NaN            NaN        NaN          USA      802.54      0   \n3            USA        38145.0        CCB          USA      989.09      0   \n4            NaN            NaN        NaN          USA      786.78      0   \n\n  Transaction_Type  \n0       WITHDRAWAL  \n1    QUICK-PAYMENT  \n2     DEPOSIT-CASH  \n3        PAY-CHECK  \n4    DEPOSIT-CHECK  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Sender_Id</th>\n      <th>Bene_Id</th>\n      <th>Sender_Account</th>\n      <th>Bene_Account</th>\n      <th>Sender_Country</th>\n      <th>Sender_Sector</th>\n      <th>Sender_lob</th>\n      <th>Bene_Country</th>\n      <th>USD_amount</th>\n      <th>Label</th>\n      <th>Transaction_Type</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>JPMC-CLIENT-10098</td>\n      <td>NaN</td>\n      <td>ACCOUNT-10108</td>\n      <td>NaN</td>\n      <td>USA</td>\n      <td>35537.0</td>\n      <td>CCB</td>\n      <td>NaN</td>\n      <td>558.43</td>\n      <td>0</td>\n      <td>WITHDRAWAL</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>JPMC-CLIENT-10098</td>\n      <td>CLIENT-10100</td>\n      <td>ACCOUNT-10109</td>\n      <td>ACCOUNT-10106</td>\n      <td>USA</td>\n      <td>15287.0</td>\n      <td>CCB</td>\n      <td>CANADA</td>\n      <td>622.78</td>\n      <td>0</td>\n      <td>QUICK-PAYMENT</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>NaN</td>\n      <td>JPMC-CLIENT-9812</td>\n      <td>NaN</td>\n      <td>ACCOUNT-9826</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>USA</td>\n      <td>802.54</td>\n      <td>0</td>\n      <td>DEPOSIT-CASH</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>JPMC-CLIENT-9812</td>\n      <td>JPMC-CLIENT-9814</td>\n      <td>ACCOUNT-9825</td>\n      <td>ACCOUNT-9824</td>\n      <td>USA</td>\n      <td>38145.0</td>\n      <td>CCB</td>\n      <td>USA</td>\n      <td>989.09</td>\n      <td>0</td>\n      <td>PAY-CHECK</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>NaN</td>\n      <td>JPMC-CLIENT-9789</td>\n      <td>NaN</td>\n      <td>ACCOUNT-9800</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>USA</td>\n      <td>786.78</td>\n      <td>0</td>\n      <td>DEPOSIT-CHECK</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"print(finance_dataset['Sender_lob'].nunique())","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"WKCB5hJQ1aBL","outputId":"8468e64b-8298-4ab8-df4b-30b8cabda54d","execution":{"iopub.status.busy":"2024-05-13T02:49:56.065393Z","iopub.execute_input":"2024-05-13T02:49:56.065864Z","iopub.status.idle":"2024-05-13T02:49:56.200965Z","shell.execute_reply.started":"2024-05-13T02:49:56.065819Z","shell.execute_reply":"2024-05-13T02:49:56.199212Z"},"trusted":true},"execution_count":673,"outputs":[{"name":"stdout","text":"1\n","output_type":"stream"}]},{"cell_type":"code","source":"# drop sender_lob since these are just one number\nfinance_dataset = finance_dataset.drop(columns = ['Sender_lob','Sender_Account','Bene_Account'],axis = 'columns')","metadata":{"id":"lvaU82zl3FQt","execution":{"iopub.status.busy":"2024-05-13T02:49:56.202919Z","iopub.execute_input":"2024-05-13T02:49:56.204149Z","iopub.status.idle":"2024-05-13T02:49:56.297158Z","shell.execute_reply.started":"2024-05-13T02:49:56.204079Z","shell.execute_reply":"2024-05-13T02:49:56.295806Z"},"trusted":true},"execution_count":674,"outputs":[]},{"cell_type":"code","source":"finance_dataset.loc[finance_dataset['Label'] == 1].isnull().sum()","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"aenWmEri1yU1","outputId":"efa01238-9f08-4e01-fc77-bec32c45777f","execution":{"iopub.status.busy":"2024-05-13T02:49:56.299503Z","iopub.execute_input":"2024-05-13T02:49:56.299920Z","iopub.status.idle":"2024-05-13T02:49:56.353067Z","shell.execute_reply.started":"2024-05-13T02:49:56.299884Z","shell.execute_reply":"2024-05-13T02:49:56.351591Z"},"trusted":true},"execution_count":675,"outputs":[{"execution_count":675,"output_type":"execute_result","data":{"text/plain":"Sender_Id           4121\nBene_Id             5136\nSender_Country      4121\nSender_Sector       4121\nBene_Country        5136\nUSD_amount             0\nLabel                  0\nTransaction_Type       0\ndtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"print((finance_dataset['Label'] == 1).sum())","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ojNkRchP3bjd","outputId":"924cb238-3d7b-4924-8f5d-158859eb42b1","execution":{"iopub.status.busy":"2024-05-13T02:49:56.354777Z","iopub.execute_input":"2024-05-13T02:49:56.356573Z","iopub.status.idle":"2024-05-13T02:49:56.367252Z","shell.execute_reply.started":"2024-05-13T02:49:56.356535Z","shell.execute_reply":"2024-05-13T02:49:56.365547Z"},"trusted":true},"execution_count":676,"outputs":[{"name":"stdout","text":"30819\n","output_type":"stream"}]},{"cell_type":"code","source":"plt.figure(figsize = (15, 8))\nax=sns.countplot(data =  finance_dataset, x = \"Transaction_Type\", hue=\"Label\", palette = 'Set1')\nplt.title('Fraud and Non Fraud Transactions before removing null values')\nfor p in ax.patches:\n        ax.annotate('{:.1f}'.format(p.get_height()), (p.get_x()+0.01, p.get_height()+10000))","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":556},"id":"3knhul2S5I5a","outputId":"b28f9fcb-8ab7-4903-aa47-7ecbc2209390","execution":{"iopub.status.busy":"2024-05-13T02:49:56.368914Z","iopub.execute_input":"2024-05-13T02:49:56.369339Z","iopub.status.idle":"2024-05-13T02:49:58.934770Z","shell.execute_reply.started":"2024-05-13T02:49:56.369305Z","shell.execute_reply":"2024-05-13T02:49:58.933226Z"},"trusted":true},"execution_count":677,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1500x800 with 1 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"# finance_dataset = finance_dataset.dropna()","metadata":{"id":"knbiS6iM34C9","execution":{"iopub.status.busy":"2024-05-13T02:49:58.936483Z","iopub.execute_input":"2024-05-13T02:49:58.936887Z","iopub.status.idle":"2024-05-13T02:49:58.943472Z","shell.execute_reply.started":"2024-05-13T02:49:58.936848Z","shell.execute_reply":"2024-05-13T02:49:58.941985Z"},"trusted":true},"execution_count":678,"outputs":[]},{"cell_type":"markdown","source":"# **Handling Null Values**","metadata":{}},{"cell_type":"code","source":"finance_dataset.loc[finance_dataset['Label'] == 1].isnull().sum()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:49:58.946284Z","iopub.execute_input":"2024-05-13T02:49:58.946768Z","iopub.status.idle":"2024-05-13T02:49:59.007076Z","shell.execute_reply.started":"2024-05-13T02:49:58.946722Z","shell.execute_reply":"2024-05-13T02:49:59.005570Z"},"trusted":true},"execution_count":679,"outputs":[{"execution_count":679,"output_type":"execute_result","data":{"text/plain":"Sender_Id           4121\nBene_Id             5136\nSender_Country      4121\nSender_Sector       4121\nBene_Country        5136\nUSD_amount             0\nLabel                  0\nTransaction_Type       0\ndtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"## Handling Null values for Sender-sector field using mean of \"fraud\" and \"non-fraud\"\n\ndata = pd.Series(finance_dataset['Sender_Sector'])\nnan_indices = data.isna()\nLabel = pd.Series(finance_dataset['Label'])\nmean_1,cntr1 = 0,0\nmean_0,cntr0 = 0,0\nfor i in range(len(nan_indices)):\n  if nan_indices[i]==0 and (Label[i] == 1):\n    mean_1 += data[i]\n    cntr1 += 1\n  elif nan_indices[i]==0 and (Label[i] == 0):\n    mean_0 += data[i]\n    cntr0 += 1\n\nmean_1 /= cntr1\nmean_0 /= cntr0\n\nfor i in range(len(nan_indices)):\n  if nan_indices[i]==1 and (Label[i] == 1):\n    data[i] = mean_1\n  elif nan_indices[i]==1 and (Label[i] == 0):\n    data[i] = mean_0","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:49:59.011707Z","iopub.execute_input":"2024-05-13T02:49:59.012187Z","iopub.status.idle":"2024-05-13T02:51:18.483809Z","shell.execute_reply.started":"2024-05-13T02:49:59.012152Z","shell.execute_reply":"2024-05-13T02:51:18.482174Z"},"trusted":true},"execution_count":680,"outputs":[]},{"cell_type":"code","source":"print(\"Mean of sender sector with Label 1:\",mean_1)\nprint(\"Mean of sender sector with Label 0:\",mean_0)\nfinance_dataset['Sender_Sector'] = data","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:51:18.488562Z","iopub.execute_input":"2024-05-13T02:51:18.489204Z","iopub.status.idle":"2024-05-13T02:51:18.498434Z","shell.execute_reply.started":"2024-05-13T02:51:18.489168Z","shell.execute_reply":"2024-05-13T02:51:18.496876Z"},"trusted":true},"execution_count":681,"outputs":[{"name":"stdout","text":"Mean of sender sector with Label 1: 25075.31878792419\nMean of sender sector with Label 0: 25020.183490567168\n","output_type":"stream"}]},{"cell_type":"code","source":"## Handling Null Values for Sender_Country and Bene_Country field using \"unknown field\"\nsender_country_data = pd.Series(finance_dataset['Sender_Country'])\nnan_indices = sender_country_data.isna()\nLabel = pd.Series(finance_dataset['Label'])\nfor i in range(len(nan_indices)):\n  if nan_indices[i]:\n    sender_country_data[i] = \"UNKNOWN\"\nfinance_dataset['Sender_Country'] = sender_country_data\n\nbene_country_data = pd.Series(finance_dataset['Bene_Country'])\nnan_indices = bene_country_data.isna()\nLabel = pd.Series(finance_dataset['Label'])\nfor i in range(len(nan_indices)):\n  if nan_indices[i]:\n    bene_country_data[i] = \"UNKNOWN\"\nfinance_dataset['Sender_Country'] = bene_country_data","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:51:18.500201Z","iopub.execute_input":"2024-05-13T02:51:18.500842Z","iopub.status.idle":"2024-05-13T02:51:40.895166Z","shell.execute_reply.started":"2024-05-13T02:51:18.500806Z","shell.execute_reply":"2024-05-13T02:51:40.893444Z"},"trusted":true},"execution_count":682,"outputs":[]},{"cell_type":"code","source":"finance_dataset.loc[finance_dataset['Label'] == 1].isnull().sum()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:51:40.896902Z","iopub.execute_input":"2024-05-13T02:51:40.897297Z","iopub.status.idle":"2024-05-13T02:51:40.952073Z","shell.execute_reply.started":"2024-05-13T02:51:40.897264Z","shell.execute_reply":"2024-05-13T02:51:40.950630Z"},"trusted":true},"execution_count":683,"outputs":[{"execution_count":683,"output_type":"execute_result","data":{"text/plain":"Sender_Id           4121\nBene_Id             5136\nSender_Country         0\nSender_Sector          0\nBene_Country           0\nUSD_amount             0\nLabel                  0\nTransaction_Type       0\ndtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"\"\"\"Handling NUll values in Sender_Id and Bene_Id using following strategy:\nThere are total 5 parties involved in the transactions: [JP-CLIENT,JP-COMPANY,COMPANY,CLIENT,BILL-COMPANY]\nwhich are encoded as: [JCL,JCOM,COM,CLT,BCO]\n\"\"\"\n\ndef update_labels(dataset, label_prefix, new_label):\n    sender_indices = dataset['Sender_Id'].str.startswith(label_prefix)\n    bene_indices = dataset['Bene_Id'].str.startswith(label_prefix)\n    \n    # Check for null values before updating labels\n    sender_null_indices = sender_indices & dataset['Sender_Id'].notnull()\n    bene_null_indices = bene_indices & dataset['Bene_Id'].notnull()\n    \n    dataset.loc[sender_null_indices, 'Sender_Id'] = new_label\n    dataset.loc[bene_null_indices, 'Bene_Id'] = new_label\n\n# Define label mappings\nlabel_mappings = {\n    'COMPANY': 'COM',\n    'BILL-COMPANY': 'BCO',\n    'CLIENT': 'CLT',\n    'JPMC-COMPANY': 'JCO',\n    'JPMC-CLIENT': 'JCL'\n}\n\n# Apply label updates for each label type\nfor prefix, new_label in label_mappings.items():\n    update_labels(finance_dataset, prefix, new_label)","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:51:40.953845Z","iopub.execute_input":"2024-05-13T02:51:40.954361Z","iopub.status.idle":"2024-05-13T02:51:56.115764Z","shell.execute_reply.started":"2024-05-13T02:51:40.954327Z","shell.execute_reply":"2024-05-13T02:51:56.114167Z"},"trusted":true},"execution_count":684,"outputs":[]},{"cell_type":"code","source":"\"\"\"Handling NUll values in Sender_Id and Bene_Id using following strategy:\n\nTHIS IS THE DATA OBTAINED WHEN ALL NULL VALUES ARE DROPPED\nNumber of fraud transactions according to type are below:\n send_rec\nJCLCLT    8883\nJCLBCO    3805\nCLTJCL    3676\nJCLJCL    1734\nJCLCOM    1731\nJCLJCO     723\nBCOJCL     619\nCOMJCL     270\nJCOJCL     121\nName: count, dtype: int64 \n\nNumber of valid transactions according to type are below:\n send_rec\nJCLBCO    358360\nJCLCLT    298159\nCLTJCL    106932\nJCLJCL     86698\nJCLCOM     61753\nCOMJCL     58934\nJCLJCO     26322\nJCOJCL     24892\nBCOJCL     19786\n\nBASED ON THE MAX CRITERIA VALUES ARE ASSIGNED TO EACH COMBINATION\n\n\"\"\"\nsender_data = pd.Series(finance_dataset['Sender_Id'])\nbene_data = pd.Series(finance_dataset['Bene_Id'])\nnan_indices_sender = sender_data.isna()\nprint(nan_indices)\nLabel = pd.Series(finance_dataset['Label'])\n\nfor i in range(len(nan_indices_sender)):\n  if nan_indices_sender[i] and bene_data[i] == 'JCL':\n    sender_data[i] = 'CLT'\n  elif nan_indices_sender[i]:\n    sender_data[i] = 'JCL'\n\nnan_indices_bene = bene_data.isna()\nfor i in range(len(nan_indices_bene)):\n  if nan_indices_bene[i] and sender_data[i] == 'JCL':\n    if Label[i] == 1:\n      bene_data[i] = 'CLT'\n    else:\n      bene_data[i] = 'BCO'\n  elif nan_indices_bene[i]:\n    bene_data[i] = 'JCL'\n\nfinance_dataset['Bene_Id'] = bene_data\nfinance_dataset['Sender_Id'] = sender_data\n  # elif i == m.isnan(i):\n  #   print(True)","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:51:56.117737Z","iopub.execute_input":"2024-05-13T02:51:56.118242Z","iopub.status.idle":"2024-05-13T02:52:35.152391Z","shell.execute_reply.started":"2024-05-13T02:51:56.118196Z","shell.execute_reply":"2024-05-13T02:52:35.151313Z"},"trusted":true},"execution_count":685,"outputs":[{"name":"stdout","text":"0           True\n1          False\n2          False\n3          False\n4          False\n           ...  \n1498172    False\n1498173    False\n1498174    False\n1498175    False\n1498176    False\nName: Bene_Country, Length: 1498177, dtype: bool\n","output_type":"stream"}]},{"cell_type":"code","source":"## ALL NULL VALUES ARE HANDLED\nfinance_dataset.loc[finance_dataset['Label'] == 1].isnull().sum()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:52:35.154140Z","iopub.execute_input":"2024-05-13T02:52:35.155663Z","iopub.status.idle":"2024-05-13T02:52:35.209259Z","shell.execute_reply.started":"2024-05-13T02:52:35.155614Z","shell.execute_reply":"2024-05-13T02:52:35.207575Z"},"trusted":true},"execution_count":686,"outputs":[{"execution_count":686,"output_type":"execute_result","data":{"text/plain":"Sender_Id           0\nBene_Id             0\nSender_Country      0\nSender_Sector       0\nBene_Country        0\nUSD_amount          0\nLabel               0\nTransaction_Type    0\ndtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"finance_dataset.head()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:52:35.221770Z","iopub.execute_input":"2024-05-13T02:52:35.222246Z","iopub.status.idle":"2024-05-13T02:52:35.246065Z","shell.execute_reply.started":"2024-05-13T02:52:35.222204Z","shell.execute_reply":"2024-05-13T02:52:35.245173Z"},"trusted":true},"execution_count":688,"outputs":[{"execution_count":688,"output_type":"execute_result","data":{"text/plain":"  Sender_Id Bene_Id Sender_Country  Sender_Sector Bene_Country  USD_amount  \\\n0       JCL     BCO        UNKNOWN   35537.000000      UNKNOWN      558.43   \n1       JCL     CLT         CANADA   15287.000000       CANADA      622.78   \n2       CLT     JCL            USA   25020.183491          USA      802.54   \n3       JCL     JCL            USA   38145.000000          USA      989.09   \n4       CLT     JCL            USA   25020.183491          USA      786.78   \n\n   Label Transaction_Type  \n0      0       WITHDRAWAL  \n1      0    QUICK-PAYMENT  \n2      0     DEPOSIT-CASH  \n3      0        PAY-CHECK  \n4      0    DEPOSIT-CHECK  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Sender_Id</th>\n      <th>Bene_Id</th>\n      <th>Sender_Country</th>\n      <th>Sender_Sector</th>\n      <th>Bene_Country</th>\n      <th>USD_amount</th>\n      <th>Label</th>\n      <th>Transaction_Type</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>JCL</td>\n      <td>BCO</td>\n      <td>UNKNOWN</td>\n      <td>35537.000000</td>\n      <td>UNKNOWN</td>\n      <td>558.43</td>\n      <td>0</td>\n      <td>WITHDRAWAL</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>JCL</td>\n      <td>CLT</td>\n      <td>CANADA</td>\n      <td>15287.000000</td>\n      <td>CANADA</td>\n      <td>622.78</td>\n      <td>0</td>\n      <td>QUICK-PAYMENT</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>CLT</td>\n      <td>JCL</td>\n      <td>USA</td>\n      <td>25020.183491</td>\n      <td>USA</td>\n      <td>802.54</td>\n      <td>0</td>\n      <td>DEPOSIT-CASH</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>JCL</td>\n      <td>JCL</td>\n      <td>USA</td>\n      <td>38145.000000</td>\n      <td>USA</td>\n      <td>989.09</td>\n      <td>0</td>\n      <td>PAY-CHECK</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>CLT</td>\n      <td>JCL</td>\n      <td>USA</td>\n      <td>25020.183491</td>\n      <td>USA</td>\n      <td>786.78</td>\n      <td>0</td>\n      <td>DEPOSIT-CHECK</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"finance_dataset.isnull().any()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:52:35.255235Z","iopub.execute_input":"2024-05-13T02:52:35.256190Z","iopub.status.idle":"2024-05-13T02:52:36.058073Z","shell.execute_reply.started":"2024-05-13T02:52:35.256143Z","shell.execute_reply":"2024-05-13T02:52:36.056560Z"},"trusted":true},"execution_count":689,"outputs":[{"execution_count":689,"output_type":"execute_result","data":{"text/plain":"Sender_Id           False\nBene_Id             False\nSender_Country      False\nSender_Sector       False\nBene_Country        False\nUSD_amount          False\nLabel               False\nTransaction_Type    False\ndtype: bool"},"metadata":{}}]},{"cell_type":"markdown","source":"CheckPoint1: A significant drop in fraud cases after removing null value. Also, observe the plots entries with \"Exchange\" field has been deleted.","metadata":{"id":"zEj25sdw4ZZA"}},{"cell_type":"code","source":"print((finance_dataset['Label'] == 1).sum())","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"jV-mBK-I4G-H","outputId":"2b794caf-9627-4aae-a0ca-25a785d2007c","execution":{"iopub.status.busy":"2024-05-13T02:52:36.059627Z","iopub.execute_input":"2024-05-13T02:52:36.060005Z","iopub.status.idle":"2024-05-13T02:52:36.070293Z","shell.execute_reply.started":"2024-05-13T02:52:36.059974Z","shell.execute_reply":"2024-05-13T02:52:36.068601Z"},"trusted":true},"execution_count":690,"outputs":[{"name":"stdout","text":"30819\n","output_type":"stream"}]},{"cell_type":"markdown","source":"EDA","metadata":{"id":"9pumorPS4n6y"}},{"cell_type":"code","source":"plt.figure(figsize = (15, 8))\nax=sns.countplot(data =  finance_dataset, x = \"Transaction_Type\", hue=\"Label\", palette = 'Set1')\nplt.title('Fraud and Non Fraud Transactions')\nfor p in ax.patches:\n        ax.annotate('{:.1f}'.format(p.get_height()), (p.get_x()+0.01, p.get_height()+10000))","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":556},"id":"3npwH05y4iec","outputId":"7c42bb2f-ddb1-43d2-a6ef-07db820a7e7c","execution":{"iopub.status.busy":"2024-05-13T02:52:36.072009Z","iopub.execute_input":"2024-05-13T02:52:36.072413Z","iopub.status.idle":"2024-05-13T02:52:38.534479Z","shell.execute_reply.started":"2024-05-13T02:52:36.072372Z","shell.execute_reply":"2024-05-13T02:52:38.532958Z"},"trusted":true},"execution_count":691,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1500x800 with 1 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"},"metadata":{}}]},{"cell_type":"code","source":"print(finance_dataset['Sender_Id'].nunique())","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"-Ubab03u5S0h","outputId":"4d8d4768-2981-4d70-cdff-adc30ac81fc1","execution":{"iopub.status.busy":"2024-05-13T02:52:38.536591Z","iopub.execute_input":"2024-05-13T02:52:38.537749Z","iopub.status.idle":"2024-05-13T02:52:38.659723Z","shell.execute_reply.started":"2024-05-13T02:52:38.537700Z","shell.execute_reply":"2024-05-13T02:52:38.658207Z"},"trusted":true},"execution_count":692,"outputs":[{"name":"stdout","text":"5\n","output_type":"stream"}]},{"cell_type":"code","source":"finance_dataset.head(20)\n\nlst_of_sender = []\nfor i in finance_dataset['Sender_Id']:\n  str_so_far = \"\"\n  for ch in i:\n    if ch.isdigit():\n      break\n    else:\n      str_so_far += ch\n  lst_of_sender.append(str_so_far)\n\nprint(np.unique(np.array(lst_of_sender)))\n\nlst_of_bene = []\nfor i in finance_dataset['Bene_Id']:\n  str_so_far = \"\"\n  for ch in i:\n    if ch.isdigit():\n      break\n    else:\n      str_so_far += ch\n  lst_of_bene.append(str_so_far)\n\nprint(np.unique(np.array(lst_of_bene)))","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"IpRwq1u1AwMR","outputId":"92e4cf62-5f4c-4c88-8bf5-7750a35f211b","execution":{"iopub.status.busy":"2024-05-13T02:52:38.668964Z","iopub.execute_input":"2024-05-13T02:52:38.669287Z","iopub.status.idle":"2024-05-13T02:52:45.163754Z","shell.execute_reply.started":"2024-05-13T02:52:38.669259Z","shell.execute_reply":"2024-05-13T02:52:45.162824Z"},"trusted":true},"execution_count":694,"outputs":[{"name":"stdout","text":"['BCO' 'CLT' 'COM' 'JCL' 'JCO']\n['BCO' 'CLT' 'COM' 'JCL' 'JCO']\n","output_type":"stream"}]},{"cell_type":"code","source":"quick_fraud = finance_dataset[((finance_dataset['Transaction_Type']=='QUICK-PAYMENT') & finance_dataset['Label']==1)]\nquick_fraud['Sender_Id'].value_counts()","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"sJrnw0zJEtUA","outputId":"94113718-2a93-4345-9b29-bfe1e41abb76","execution":{"iopub.status.busy":"2024-05-13T02:52:45.165050Z","iopub.execute_input":"2024-05-13T02:52:45.166174Z","iopub.status.idle":"2024-05-13T02:52:45.475678Z","shell.execute_reply.started":"2024-05-13T02:52:45.166139Z","shell.execute_reply":"2024-05-13T02:52:45.474223Z"},"trusted":true},"execution_count":695,"outputs":[{"execution_count":695,"output_type":"execute_result","data":{"text/plain":"Sender_Id\nJCL    5798\nCLT    1671\nBCO     284\nCOM     125\nJCO      57\nName: count, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"pay_check_fraud = finance_dataset[((finance_dataset['Transaction_Type']=='PAY-CHECK') & finance_dataset['Label']==1)]\npay_check_fraud['Sender_Id'].value_counts()","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"uFbZCzOCFObO","outputId":"930cb9fd-8006-4607-8bfa-8c070c9c66d4","execution":{"iopub.status.busy":"2024-05-13T02:52:45.480616Z","iopub.execute_input":"2024-05-13T02:52:45.481413Z","iopub.status.idle":"2024-05-13T02:52:45.793513Z","shell.execute_reply.started":"2024-05-13T02:52:45.481374Z","shell.execute_reply":"2024-05-13T02:52:45.792173Z"},"trusted":true},"execution_count":696,"outputs":[{"execution_count":696,"output_type":"execute_result","data":{"text/plain":"Sender_Id\nJCL    2186\nCLT     676\nBCO     110\nCOM      53\nJCO      20\nName: count, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"make_payment_fraud = finance_dataset[((finance_dataset['Transaction_Type']=='MAKE-PAYMENT') & finance_dataset['Label']==1)]\nmake_payment_fraud['Sender_Id'].value_counts()","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"W34l8PQKFoIR","outputId":"9e4548a6-4bf3-486e-ae2e-233feedc2fe8","execution":{"iopub.status.busy":"2024-05-13T02:52:45.795308Z","iopub.execute_input":"2024-05-13T02:52:45.795691Z","iopub.status.idle":"2024-05-13T02:52:46.175818Z","shell.execute_reply.started":"2024-05-13T02:52:45.795653Z","shell.execute_reply":"2024-05-13T02:52:46.174453Z"},"trusted":true},"execution_count":697,"outputs":[{"execution_count":697,"output_type":"execute_result","data":{"text/plain":"Sender_Id\nJCL    6716\nCLT     650\nBCO     118\nCOM      39\nJCO      20\nName: count, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"move_funds_fraud = finance_dataset[((finance_dataset['Transaction_Type']=='MOVE-FUNDS') & finance_dataset['Label']==1)]\nmove_funds_fraud['Sender_Id'].value_counts()","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"5DddrM_NFxMf","outputId":"e47845c4-1288-41ce-9f84-f20c20c4fff0","execution":{"iopub.status.busy":"2024-05-13T02:52:46.177688Z","iopub.execute_input":"2024-05-13T02:52:46.178082Z","iopub.status.idle":"2024-05-13T02:52:46.474730Z","shell.execute_reply.started":"2024-05-13T02:52:46.178050Z","shell.execute_reply":"2024-05-13T02:52:46.473211Z"},"trusted":true},"execution_count":698,"outputs":[{"execution_count":698,"output_type":"execute_result","data":{"text/plain":"Sender_Id\nJCL    2176\nCLT     679\nBCO     107\nCOM      53\nJCO      24\nName: count, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"exchange_fraud = finance_dataset[((finance_dataset['Transaction_Type']=='EXCHANGE') & finance_dataset['Label']==1)]\nexchange_fraud['Sender_Id'].value_counts()","metadata":{"id":"f6HlhW6xIKRH","execution":{"iopub.status.busy":"2024-05-13T02:52:46.476785Z","iopub.execute_input":"2024-05-13T02:52:46.477184Z","iopub.status.idle":"2024-05-13T02:52:46.766946Z","shell.execute_reply.started":"2024-05-13T02:52:46.477137Z","shell.execute_reply":"2024-05-13T02:52:46.765604Z"},"trusted":true},"execution_count":699,"outputs":[{"execution_count":699,"output_type":"execute_result","data":{"text/plain":"Sender_Id\nJCL    2526\nName: count, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"deposit_check_fraud = finance_dataset[((finance_dataset['Transaction_Type']=='DEPOSIT-CHECK') & finance_dataset['Label']==1)]\ndeposit_check_fraud['Sender_Id'].value_counts()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:52:46.768676Z","iopub.execute_input":"2024-05-13T02:52:46.769061Z","iopub.status.idle":"2024-05-13T02:52:47.062176Z","shell.execute_reply.started":"2024-05-13T02:52:46.769028Z","shell.execute_reply":"2024-05-13T02:52:47.060597Z"},"trusted":true},"execution_count":700,"outputs":[{"execution_count":700,"output_type":"execute_result","data":{"text/plain":"Sender_Id\nCLT    1349\nName: count, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"deposit_cash_fraud = finance_dataset[((finance_dataset['Transaction_Type']=='DEPOSIT-CASH') & finance_dataset['Label']==1)]\ndeposit_cash_fraud['Sender_Id'].value_counts()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:52:47.064428Z","iopub.execute_input":"2024-05-13T02:52:47.064911Z","iopub.status.idle":"2024-05-13T02:52:47.368809Z","shell.execute_reply.started":"2024-05-13T02:52:47.064860Z","shell.execute_reply":"2024-05-13T02:52:47.367356Z"},"trusted":true},"execution_count":701,"outputs":[{"execution_count":701,"output_type":"execute_result","data":{"text/plain":"Sender_Id\nCLT    2772\nName: count, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"withdrawal_fraud = finance_dataset[((finance_dataset['Transaction_Type']=='WITHDRAWAL') & finance_dataset['Label']==1)]\nwithdrawal_fraud['Sender_Id'].value_counts()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:52:47.370225Z","iopub.execute_input":"2024-05-13T02:52:47.370553Z","iopub.status.idle":"2024-05-13T02:52:47.665698Z","shell.execute_reply.started":"2024-05-13T02:52:47.370526Z","shell.execute_reply":"2024-05-13T02:52:47.664788Z"},"trusted":true},"execution_count":702,"outputs":[{"execution_count":702,"output_type":"execute_result","data":{"text/plain":"Sender_Id\nJCL    2610\nName: count, dtype: int64"},"metadata":{}}]},{"cell_type":"markdown","source":"**Insights : In most fraud cases class jpmc-client is involved**","metadata":{"id":"S2wPil_RF8Fc"}},{"cell_type":"markdown","source":"**Feature Engineering**","metadata":{"id":"qLinjQfFESSf"}},{"cell_type":"code","source":"data = finance_dataset.copy()\ndata['send_rec'] = np.nan\n\ndata.loc[finance_dataset.Sender_Id.str.contains('BCO') & finance_dataset.Bene_Id.str.contains('BCO'), 'send_rec'] = 'BCOBCO'\ndata.loc[finance_dataset.Sender_Id.str.contains('BCO') & finance_dataset.Bene_Id.str.contains('CLT'), 'send_rec'] = 'BCOCLT'\ndata.loc[finance_dataset.Sender_Id.str.contains('BCO') & finance_dataset.Bene_Id.str.contains('COM'), 'send_rec'] = 'BCOCOM'\ndata.loc[finance_dataset.Sender_Id.str.contains('BCO') & finance_dataset.Bene_Id.str.contains('JCL'), 'send_rec'] = 'BCOJCL'\ndata.loc[finance_dataset.Sender_Id.str.contains('BCO') & finance_dataset.Bene_Id.str.contains('JCO'), 'send_rec'] = 'BCOJCO'\n\ndata.loc[finance_dataset.Sender_Id.str.contains('CLT') & finance_dataset.Bene_Id.str.contains('BCO'), 'send_rec'] = 'CLTBCO'\ndata.loc[finance_dataset.Sender_Id.str.contains('CLT') & finance_dataset.Bene_Id.str.contains('CLT'), 'send_rec'] = 'CLTCLT'\ndata.loc[finance_dataset.Sender_Id.str.contains('CLT') & finance_dataset.Bene_Id.str.contains('COM'), 'send_rec'] = 'CLTCOM'\ndata.loc[finance_dataset.Sender_Id.str.contains('CLT') & finance_dataset.Bene_Id.str.contains('JCL'), 'send_rec'] = 'CLTJCL'\ndata.loc[finance_dataset.Sender_Id.str.contains('CLT') & finance_dataset.Bene_Id.str.contains('JCO'), 'send_rec'] = 'CLTJCO'\n\ndata.loc[finance_dataset.Sender_Id.str.contains('COM') & finance_dataset.Bene_Id.str.contains('BCO'), 'send_rec'] = 'COMBCO'\ndata.loc[finance_dataset.Sender_Id.str.contains('COM') & finance_dataset.Bene_Id.str.contains('CLT'), 'send_rec'] = 'COMCLT'\ndata.loc[finance_dataset.Sender_Id.str.contains('COM') & finance_dataset.Bene_Id.str.contains('COM'), 'send_rec'] = 'COMCOM'\ndata.loc[finance_dataset.Sender_Id.str.contains('COM') & finance_dataset.Bene_Id.str.contains('JCL'), 'send_rec'] = 'COMJCL'\ndata.loc[finance_dataset.Sender_Id.str.contains('COM') & finance_dataset.Bene_Id.str.contains('JCO'), 'send_rec'] = 'COMJCO'\n\ndata.loc[finance_dataset.Sender_Id.str.contains('JCL') & finance_dataset.Bene_Id.str.contains('BCO'), 'send_rec'] = 'JCLBCO'\ndata.loc[finance_dataset.Sender_Id.str.contains('JCL') & finance_dataset.Bene_Id.str.contains('CLT'), 'send_rec'] = 'JCLCLT'\ndata.loc[finance_dataset.Sender_Id.str.contains('JCL') & finance_dataset.Bene_Id.str.contains('COM'), 'send_rec'] = 'JCLCOM'\ndata.loc[finance_dataset.Sender_Id.str.contains('JCL') & finance_dataset.Bene_Id.str.contains('JCL'), 'send_rec'] = 'JCLJCL'\ndata.loc[finance_dataset.Sender_Id.str.contains('JCL') & finance_dataset.Bene_Id.str.contains('JCO'), 'send_rec'] = 'JCLJCO'\n\ndata.loc[finance_dataset.Sender_Id.str.contains('JCO') & finance_dataset.Bene_Id.str.contains('BCO'), 'send_rec'] = 'JCOBCO'\ndata.loc[finance_dataset.Sender_Id.str.contains('JCO') & finance_dataset.Bene_Id.str.contains('CLT'), 'send_rec'] = 'JCOCLT'\ndata.loc[finance_dataset.Sender_Id.str.contains('JCO') & finance_dataset.Bene_Id.str.contains('COM'), 'send_rec'] = 'JCOCOM'\ndata.loc[finance_dataset.Sender_Id.str.contains('JCO') & finance_dataset.Bene_Id.str.contains('JCL'), 'send_rec'] = 'JCOJCL'\ndata.loc[finance_dataset.Sender_Id.str.contains('JCO') & finance_dataset.Bene_Id.str.contains('JCO'), 'send_rec'] = 'JCOJCO'","metadata":{"id":"uwrzfhzcERtg","execution":{"iopub.status.busy":"2024-05-13T02:52:47.667185Z","iopub.execute_input":"2024-05-13T02:52:47.667550Z","iopub.status.idle":"2024-05-13T02:53:26.076089Z","shell.execute_reply.started":"2024-05-13T02:52:47.667519Z","shell.execute_reply":"2024-05-13T02:53:26.074702Z"},"trusted":true},"execution_count":703,"outputs":[]},{"cell_type":"code","source":"data.drop(columns = ['Sender_Id','Bene_Id'], axis = 'columns', inplace = True)","metadata":{"id":"mUFdt_OxMq2h","execution":{"iopub.status.busy":"2024-05-13T02:53:26.077790Z","iopub.execute_input":"2024-05-13T02:53:26.078200Z","iopub.status.idle":"2024-05-13T02:53:26.183594Z","shell.execute_reply.started":"2024-05-13T02:53:26.078165Z","shell.execute_reply":"2024-05-13T02:53:26.182382Z"},"trusted":true},"execution_count":704,"outputs":[]},{"cell_type":"code","source":"cols = data.columns.tolist()\nnew_position = 0\n\ncols.insert(new_position, cols.pop(cols.index('send_rec')))\ndata = data[cols]\n\n\ncols = data.columns.tolist()\nnew_position = 2\n\ncols.insert(new_position, cols.pop(cols.index('Bene_Country')))\ndata = data[cols]\n\n\n## changing position of transaction type column\ncols = data.columns.tolist()\nnew_position = 3\n\ncols.insert(new_position, cols.pop(cols.index('Transaction_Type')))\ndata = data[cols]","metadata":{"id":"F0jlMw8FSYmX","execution":{"iopub.status.busy":"2024-05-13T02:53:26.184953Z","iopub.execute_input":"2024-05-13T02:53:26.185350Z","iopub.status.idle":"2024-05-13T02:53:26.457512Z","shell.execute_reply.started":"2024-05-13T02:53:26.185318Z","shell.execute_reply":"2024-05-13T02:53:26.456214Z"},"trusted":true},"execution_count":705,"outputs":[]},{"cell_type":"code","source":"data.head()","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"MZ7lNSGGMyzO","outputId":"8be457a5-95e8-4db4-f45d-9e621d0d3d5f","execution":{"iopub.status.busy":"2024-05-13T02:53:26.459623Z","iopub.execute_input":"2024-05-13T02:53:26.460095Z","iopub.status.idle":"2024-05-13T02:53:26.481398Z","shell.execute_reply.started":"2024-05-13T02:53:26.460049Z","shell.execute_reply":"2024-05-13T02:53:26.480199Z"},"trusted":true},"execution_count":706,"outputs":[{"execution_count":706,"output_type":"execute_result","data":{"text/plain":"  send_rec Sender_Country Bene_Country Transaction_Type  Sender_Sector  \\\n0   JCLBCO        UNKNOWN      UNKNOWN       WITHDRAWAL   35537.000000   \n1   JCLCLT         CANADA       CANADA    QUICK-PAYMENT   15287.000000   \n2   CLTJCL            USA          USA     DEPOSIT-CASH   25020.183491   \n3   JCLJCL            USA          USA        PAY-CHECK   38145.000000   \n4   CLTJCL            USA          USA    DEPOSIT-CHECK   25020.183491   \n\n   USD_amount  Label  \n0      558.43      0  \n1      622.78      0  \n2      802.54      0  \n3      989.09      0  \n4      786.78      0  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>send_rec</th>\n      <th>Sender_Country</th>\n      <th>Bene_Country</th>\n      <th>Transaction_Type</th>\n      <th>Sender_Sector</th>\n      <th>USD_amount</th>\n      <th>Label</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>JCLBCO</td>\n      <td>UNKNOWN</td>\n      <td>UNKNOWN</td>\n      <td>WITHDRAWAL</td>\n      <td>35537.000000</td>\n      <td>558.43</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>JCLCLT</td>\n      <td>CANADA</td>\n      <td>CANADA</td>\n      <td>QUICK-PAYMENT</td>\n      <td>15287.000000</td>\n      <td>622.78</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>CLTJCL</td>\n      <td>USA</td>\n      <td>USA</td>\n      <td>DEPOSIT-CASH</td>\n      <td>25020.183491</td>\n      <td>802.54</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>JCLJCL</td>\n      <td>USA</td>\n      <td>USA</td>\n      <td>PAY-CHECK</td>\n      <td>38145.000000</td>\n      <td>989.09</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>CLTJCL</td>\n      <td>USA</td>\n      <td>USA</td>\n      <td>DEPOSIT-CHECK</td>\n      <td>25020.183491</td>\n      <td>786.78</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"print((data['send_rec'] == 'BCOCLT').sum())","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:26.483069Z","iopub.execute_input":"2024-05-13T02:53:26.483486Z","iopub.status.idle":"2024-05-13T02:53:26.781959Z","shell.execute_reply.started":"2024-05-13T02:53:26.483454Z","shell.execute_reply":"2024-05-13T02:53:26.780415Z"},"trusted":true},"execution_count":707,"outputs":[{"name":"stdout","text":"0\n","output_type":"stream"}]},{"cell_type":"code","source":"fraud_trans = data[data['Label'] == 1]\nvalid_trans = data[data['Label'] == 0]\nprint('Number of fraud transactions according to type are below:\\n', fraud_trans.send_rec.value_counts(), '\\n')\nprint('Number of valid transactions according to type are below:\\n', valid_trans.send_rec.value_counts())","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"89hkylDyM-Y4","outputId":"31be3d22-f346-4ba3-c889-afba0484d14c","execution":{"iopub.status.busy":"2024-05-13T02:53:26.784020Z","iopub.execute_input":"2024-05-13T02:53:26.784550Z","iopub.status.idle":"2024-05-13T02:53:27.155532Z","shell.execute_reply.started":"2024-05-13T02:53:26.784504Z","shell.execute_reply":"2024-05-13T02:53:27.154043Z"},"trusted":true},"execution_count":708,"outputs":[{"name":"stdout","text":"Number of fraud transactions according to type are below:\n send_rec\nJCLCLT    14019\nCLTJCL     7797\nJCLBCO     3805\nJCLJCL     1734\nJCLCOM     1731\nJCLJCO      723\nBCOJCL      619\nCOMJCL      270\nJCOJCL      121\nName: count, dtype: int64 \n\nNumber of valid transactions according to type are below:\n send_rec\nJCLBCO    569117\nCLTJCL    321697\nJCLCLT    298159\nJCLJCL     86698\nJCLCOM     61753\nCOMJCL     58934\nJCLJCO     26322\nJCOJCL     24892\nBCOJCL     19786\nName: count, dtype: int64\n","output_type":"stream"}]},{"cell_type":"code","source":"data.head()\ndata.describe()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:27.158052Z","iopub.execute_input":"2024-05-13T02:53:27.158597Z","iopub.status.idle":"2024-05-13T02:53:27.356404Z","shell.execute_reply.started":"2024-05-13T02:53:27.158551Z","shell.execute_reply":"2024-05-13T02:53:27.354841Z"},"trusted":true},"execution_count":709,"outputs":[{"execution_count":709,"output_type":"execute_result","data":{"text/plain":"       Sender_Sector    USD_amount         Label\ncount   1.498177e+06  1.498177e+06  1.498177e+06\nmean    2.502132e+04  5.134698e+02  2.057100e-02\nstd     1.333586e+04  5.398089e+02  1.419431e-01\nmin     0.000000e+00  0.000000e+00  0.000000e+00\n25%     1.468100e+04  1.386900e+02  0.000000e+00\n50%     2.502018e+04  4.041600e+02  0.000000e+00\n75%     3.539000e+04  7.340700e+02  0.000000e+00\nmax     4.999900e+04  1.999894e+04  1.000000e+00","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Sender_Sector</th>\n      <th>USD_amount</th>\n      <th>Label</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>1.498177e+06</td>\n      <td>1.498177e+06</td>\n      <td>1.498177e+06</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>2.502132e+04</td>\n      <td>5.134698e+02</td>\n      <td>2.057100e-02</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>1.333586e+04</td>\n      <td>5.398089e+02</td>\n      <td>1.419431e-01</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>1.468100e+04</td>\n      <td>1.386900e+02</td>\n      <td>0.000000e+00</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>2.502018e+04</td>\n      <td>4.041600e+02</td>\n      <td>0.000000e+00</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>3.539000e+04</td>\n      <td>7.340700e+02</td>\n      <td>0.000000e+00</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>4.999900e+04</td>\n      <td>1.999894e+04</td>\n      <td>1.000000e+00</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"**Add 1 more feature \"Surge_indicator\": Creates a new column which has 1 if the transaction amount is greater than the threshold\n    else it will be 0**","metadata":{}},{"cell_type":"code","source":"finance_fraud = data[data['Label'] == 1].copy()\nfinance_valid = data[data['Label'] == 0].copy()\n\n# print(\"Financial Fraud Data Analysis\")\nfinance_fraud.describe()\nmean = np.mean(finance_fraud['USD_amount'])\nmax_ = np.max(finance_fraud['USD_amount'])\nstd_dev = np.std(data['USD_amount'])\n# print(\"Financial Non-Fraud Data Analysis\")\n# print(finance_valid.describe())","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:27.358560Z","iopub.execute_input":"2024-05-13T02:53:27.358939Z","iopub.status.idle":"2024-05-13T02:53:28.008093Z","shell.execute_reply.started":"2024-05-13T02:53:27.358908Z","shell.execute_reply":"2024-05-13T02:53:28.006233Z"},"trusted":true},"execution_count":710,"outputs":[]},{"cell_type":"code","source":"finance_fraud.describe()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:28.009860Z","iopub.execute_input":"2024-05-13T02:53:28.010241Z","iopub.status.idle":"2024-05-13T02:53:28.037392Z","shell.execute_reply.started":"2024-05-13T02:53:28.010209Z","shell.execute_reply":"2024-05-13T02:53:28.036233Z"},"trusted":true},"execution_count":711,"outputs":[{"execution_count":711,"output_type":"execute_result","data":{"text/plain":"       Sender_Sector    USD_amount    Label\ncount   30819.000000  30819.000000  30819.0\nmean    25075.318788    847.442043      1.0\nstd     13414.504284   2003.566402      0.0\nmin         0.000000    100.000000      1.0\n25%     14513.500000    254.115000      1.0\n50%     25075.318788    512.230000      1.0\n75%     35672.500000    773.975000      1.0\nmax     49999.000000  19998.940000      1.0","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Sender_Sector</th>\n      <th>USD_amount</th>\n      <th>Label</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>30819.000000</td>\n      <td>30819.000000</td>\n      <td>30819.0</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>25075.318788</td>\n      <td>847.442043</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>13414.504284</td>\n      <td>2003.566402</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>0.000000</td>\n      <td>100.000000</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>14513.500000</td>\n      <td>254.115000</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>25075.318788</td>\n      <td>512.230000</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>35672.500000</td>\n      <td>773.975000</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>49999.000000</td>\n      <td>19998.940000</td>\n      <td>1.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"finance_valid.describe()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:28.038935Z","iopub.execute_input":"2024-05-13T02:53:28.039484Z","iopub.status.idle":"2024-05-13T02:53:28.216607Z","shell.execute_reply.started":"2024-05-13T02:53:28.039451Z","shell.execute_reply":"2024-05-13T02:53:28.214960Z"},"trusted":true},"execution_count":712,"outputs":[{"execution_count":712,"output_type":"execute_result","data":{"text/plain":"       Sender_Sector    USD_amount      Label\ncount   1.467358e+06  1.467358e+06  1467358.0\nmean    2.502018e+04  5.064553e+02        0.0\nstd     1.333421e+04  4.591433e+02        0.0\nmin     0.000000e+00  0.000000e+00        0.0\n25%     1.468500e+04  1.355300e+02        0.0\n50%     2.502018e+04  4.011900e+02        0.0\n75%     3.538300e+04  7.330300e+02        0.0\nmax     4.999900e+04  1.985449e+04        0.0","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Sender_Sector</th>\n      <th>USD_amount</th>\n      <th>Label</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>1.467358e+06</td>\n      <td>1.467358e+06</td>\n      <td>1467358.0</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>2.502018e+04</td>\n      <td>5.064553e+02</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>1.333421e+04</td>\n      <td>4.591433e+02</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>1.468500e+04</td>\n      <td>1.355300e+02</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>2.502018e+04</td>\n      <td>4.011900e+02</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>3.538300e+04</td>\n      <td>7.330300e+02</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>4.999900e+04</td>\n      <td>1.985449e+04</td>\n      <td>0.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"def surge_indicator(data):\n    '''Creates a new column which has 1 if the transaction amount is greater than the threshold\n    else it will be 0'''\n    threshold = max_*(3/4)\n    data['surge']=[1 if n>threshold else 0 for n in data['USD_amount']]\n    \nsurge_indicator(data)\ndata['surge'].value_counts()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:28.218465Z","iopub.execute_input":"2024-05-13T02:53:28.218852Z","iopub.status.idle":"2024-05-13T02:53:29.396138Z","shell.execute_reply.started":"2024-05-13T02:53:28.218819Z","shell.execute_reply":"2024-05-13T02:53:29.394731Z"},"trusted":true},"execution_count":713,"outputs":[{"execution_count":713,"output_type":"execute_result","data":{"text/plain":"surge\n0    1497969\n1        208\nName: count, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"data.head()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:29.398600Z","iopub.execute_input":"2024-05-13T02:53:29.399013Z","iopub.status.idle":"2024-05-13T02:53:29.416371Z","shell.execute_reply.started":"2024-05-13T02:53:29.398979Z","shell.execute_reply":"2024-05-13T02:53:29.414911Z"},"trusted":true},"execution_count":714,"outputs":[{"execution_count":714,"output_type":"execute_result","data":{"text/plain":"  send_rec Sender_Country Bene_Country Transaction_Type  Sender_Sector  \\\n0   JCLBCO        UNKNOWN      UNKNOWN       WITHDRAWAL   35537.000000   \n1   JCLCLT         CANADA       CANADA    QUICK-PAYMENT   15287.000000   \n2   CLTJCL            USA          USA     DEPOSIT-CASH   25020.183491   \n3   JCLJCL            USA          USA        PAY-CHECK   38145.000000   \n4   CLTJCL            USA          USA    DEPOSIT-CHECK   25020.183491   \n\n   USD_amount  Label  surge  \n0      558.43      0      0  \n1      622.78      0      0  \n2      802.54      0      0  \n3      989.09      0      0  \n4      786.78      0      0  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>send_rec</th>\n      <th>Sender_Country</th>\n      <th>Bene_Country</th>\n      <th>Transaction_Type</th>\n      <th>Sender_Sector</th>\n      <th>USD_amount</th>\n      <th>Label</th>\n      <th>surge</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>JCLBCO</td>\n      <td>UNKNOWN</td>\n      <td>UNKNOWN</td>\n      <td>WITHDRAWAL</td>\n      <td>35537.000000</td>\n      <td>558.43</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>JCLCLT</td>\n      <td>CANADA</td>\n      <td>CANADA</td>\n      <td>QUICK-PAYMENT</td>\n      <td>15287.000000</td>\n      <td>622.78</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>CLTJCL</td>\n      <td>USA</td>\n      <td>USA</td>\n      <td>DEPOSIT-CASH</td>\n      <td>25020.183491</td>\n      <td>802.54</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>JCLJCL</td>\n      <td>USA</td>\n      <td>USA</td>\n      <td>PAY-CHECK</td>\n      <td>38145.000000</td>\n      <td>989.09</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>CLTJCL</td>\n      <td>USA</td>\n      <td>USA</td>\n      <td>DEPOSIT-CHECK</td>\n      <td>25020.183491</td>\n      <td>786.78</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"**Data Visualization**","metadata":{"id":"U6fXXSQlN4Pr"}},{"cell_type":"code","source":"f, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 6))\nax1 = sns.distplot(finance_dataset['USD_amount'], ax=ax1, color='y')\nax2 = sns.distplot(finance_dataset['Sender_Sector'], ax=ax2, color='r')\nax1.set_title('Distribution of USD_Amount', fontsize=13)\nax2.set_title('Distribution of sender_sector', fontsize=13)\n## The Data doesn't folow Normal Distribution and Thus filters our choice of the models","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:29.418021Z","iopub.execute_input":"2024-05-13T02:53:29.418418Z","iopub.status.idle":"2024-05-13T02:53:42.747237Z","shell.execute_reply.started":"2024-05-13T02:53:29.418385Z","shell.execute_reply":"2024-05-13T02:53:42.746220Z"},"trusted":true},"execution_count":715,"outputs":[{"execution_count":715,"output_type":"execute_result","data":{"text/plain":"Text(0.5, 1.0, 'Distribution of sender_sector')"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 1500x600 with 2 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"},"metadata":{}}]},{"cell_type":"code","source":"import matplotlib.pyplot as plt\n\nfraudulent_transactions = finance_dataset[finance_dataset['Label'] == 1]\ncountry_fraud_counts = fraudulent_transactions.groupby('Sender_Country').size()\ntop_3_countries = country_fraud_counts.nlargest(3)\nothers_count = country_fraud_counts.sum() - top_3_countries.sum()\nplot_data = pd.concat([top_3_countries, pd.Series(others_count, index=['Others'])])\n\n# Plot a pie chart with the top 3 countries and \"Others\" category\nplt.figure(figsize=(10, 8))\nplt.pie(plot_data, labels=plot_data.index, autopct='%1.1f%%')\nplt.title('Proportion of Fraudulent Transactions by Top 3 Sender Countries and Others')\n\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:42.748636Z","iopub.execute_input":"2024-05-13T02:53:42.749396Z","iopub.status.idle":"2024-05-13T02:53:47.399010Z","shell.execute_reply.started":"2024-05-13T02:53:42.749353Z","shell.execute_reply":"2024-05-13T02:53:47.397912Z"},"trusted":true},"execution_count":716,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x800 with 1 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"import pandas as pd\nimport matplotlib.pyplot as plt\nfraudulent_transactions = finance_dataset[finance_dataset['Label'] == 1]\ncountry_fraud_counts = fraudulent_transactions.groupby('Bene_Country').size()\n# Get the top 3 countries with the highest counts of fraudulent transactions\ntop_3_countries = country_fraud_counts.nlargest(3)\nothers_count = country_fraud_counts.sum() - top_3_countries.sum()\nplot_data = pd.concat([top_3_countries, pd.Series(others_count, index=['Others'])])\n# Plot a pie chart with the top 3 countries and \"Others\" category\nplt.figure(figsize=(10, 8))\nplt.pie(plot_data, labels=plot_data.index, autopct='%1.1f%%')\nplt.title('Proportion of Fraudulent Transactions by Top 3 Bene Countries and Others')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:47.400663Z","iopub.execute_input":"2024-05-13T02:53:47.401266Z","iopub.status.idle":"2024-05-13T02:53:47.651323Z","shell.execute_reply.started":"2024-05-13T02:53:47.401229Z","shell.execute_reply":"2024-05-13T02:53:47.649511Z"},"trusted":true},"execution_count":717,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x800 with 1 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"import pandas as pd\nimport matplotlib.pyplot as plt\nvalid_transactions = finance_dataset[finance_dataset['Label'] == 0]\ncountry_fraud_counts = valid_transactions.groupby('Sender_Country').size()\n# Get the top 3 countries with the highest counts of fraudulent transactions\ntop_3_countries = country_fraud_counts.nlargest(3)\nothers_count = country_fraud_counts.sum() - top_3_countries.sum()\nplot_data = pd.concat([top_3_countries, pd.Series(others_count, index=['Others'])])\nplt.figure(figsize=(10, 8))\nplt.pie(plot_data, labels=plot_data.index, autopct='%1.1f%%')\nplt.title('Proportion of Valid Transactions by Top 3 Sender Countries and Others')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:47.653921Z","iopub.execute_input":"2024-05-13T02:53:47.654530Z","iopub.status.idle":"2024-05-13T02:53:48.463982Z","shell.execute_reply.started":"2024-05-13T02:53:47.654495Z","shell.execute_reply":"2024-05-13T02:53:48.462838Z"},"trusted":true},"execution_count":718,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x800 with 1 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"import pandas as pd\nimport matplotlib.pyplot as plt\nvalid_transactions = finance_dataset[finance_dataset['Label'] == 0]\ncountry_fraud_counts = valid_transactions.groupby('Bene_Country').size()\n# Get the top 3 countries with the highest counts of fraudulent transactions\ntop_3_countries = country_fraud_counts.nlargest(3)\nothers_count = country_fraud_counts.sum() - top_3_countries.sum()\nplot_data = pd.concat([top_3_countries, pd.Series(others_count, index=['Others'])])\nplt.figure(figsize=(10, 8))\nplt.pie(plot_data, labels=plot_data.index, autopct='%1.1f%%')\nplt.title('Proportion of Valid Transactions by Top 3 Bene Countries and Others')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:48.465902Z","iopub.execute_input":"2024-05-13T02:53:48.466621Z","iopub.status.idle":"2024-05-13T02:53:49.093001Z","shell.execute_reply.started":"2024-05-13T02:53:48.466582Z","shell.execute_reply":"2024-05-13T02:53:49.091872Z"},"trusted":true},"execution_count":719,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x800 with 1 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"import matplotlib.pyplot as plt\nimport seaborn as sns\n\nplt.figure(figsize = (15, 8))\nax=sns.countplot(data =  data, x = \"send_rec\", hue=\"Label\", palette = 'Set1')\nplt.title('Fraud and Non Fraud Transactions')\nfor p in ax.patches:\n        ax.annotate('{:.1f}'.format(p.get_height()), (p.get_x()+0.01, p.get_height()+10000))","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:49.094893Z","iopub.execute_input":"2024-05-13T02:53:49.095598Z","iopub.status.idle":"2024-05-13T02:53:51.541124Z","shell.execute_reply.started":"2024-05-13T02:53:49.095561Z","shell.execute_reply":"2024-05-13T02:53:51.539803Z"},"trusted":true},"execution_count":720,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1500x800 with 1 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"},"metadata":{}}]},{"cell_type":"markdown","source":"Insights:\n1. By creating a new feature send_rec, using Sender_Id and Bene_Id. we can analyse from the plot which category is more prominent to fraud by comparing the ratio of Fraud v/s Not Fraud Transaction.\n2. We can see that Transactions with USA as Sender_Country and Bene_Country are more involved in the transactions.\n3. Other Countries include Canada, Germnay and some Countries whose data is missing.","metadata":{}},{"cell_type":"markdown","source":"**Data Pre-procesing**\n","metadata":{"id":"SNIQjZcdN8Fm"}},{"cell_type":"code","source":"## Using Label Encoding \nfrom sklearn.preprocessing import LabelEncoder\ncolumn_list = ['send_rec','Sender_Country','Bene_Country','Transaction_Type','surge']\n\nencoders = {}\n\n# Loop through each column that needs encoding\nfor column in column_list:\n    # Create a LabelEncoder for the column\n    encoder = LabelEncoder()\n    # Fit and transform the data using LabelEncoder\n    data[column] = encoder.fit_transform(data[column])\n    # Store the encoder in the dictionary for future use (if needed)\n    encoders[column] = encoder\n\n# Print the DataFrame with the encoded columns","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:51.543434Z","iopub.execute_input":"2024-05-13T02:53:51.544354Z","iopub.status.idle":"2024-05-13T02:53:53.456919Z","shell.execute_reply.started":"2024-05-13T02:53:51.544305Z","shell.execute_reply":"2024-05-13T02:53:53.455267Z"},"trusted":true},"execution_count":721,"outputs":[]},{"cell_type":"code","source":"print(data.head())\ndata.shape","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"xlKW2VwBS87K","outputId":"aba3d5e6-a248-4401-d4ad-ef7e91ef7173","execution":{"iopub.status.busy":"2024-05-13T02:53:53.459671Z","iopub.execute_input":"2024-05-13T02:53:53.460220Z","iopub.status.idle":"2024-05-13T02:53:53.474114Z","shell.execute_reply.started":"2024-05-13T02:53:53.460170Z","shell.execute_reply":"2024-05-13T02:53:53.472632Z"},"trusted":true},"execution_count":722,"outputs":[{"name":"stdout","text":"   send_rec  Sender_Country  Bene_Country  Transaction_Type  Sender_Sector  \\\n0         3             238           238                 7   35537.000000   \n1         4              40            40                 6   15287.000000   \n2         1             240           240                 0   25020.183491   \n3         6             240           240                 5   38145.000000   \n4         1             240           240                 1   25020.183491   \n\n   USD_amount  Label  surge  \n0      558.43      0      0  \n1      622.78      0      0  \n2      802.54      0      0  \n3      989.09      0      0  \n4      786.78      0      0  \n","output_type":"stream"},{"execution_count":722,"output_type":"execute_result","data":{"text/plain":"(1498177, 8)"},"metadata":{}}]},{"cell_type":"markdown","source":"CheckPoint: Pandas converting it to 516 dimensions ","metadata":{}},{"cell_type":"code","source":"X = data.drop('Label',axis = 1)\ny = data.Label\n\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.30, stratify = data.Label)\n# X_train_c = X_train.copy()\nsc = StandardScaler()\nX_train = sc.fit_transform(X_train)\nX_test = sc.transform(X_test)","metadata":{"id":"sOn0LYHeTWZx","execution":{"iopub.status.busy":"2024-05-13T02:53:53.476505Z","iopub.execute_input":"2024-05-13T02:53:53.476986Z","iopub.status.idle":"2024-05-13T02:53:54.772239Z","shell.execute_reply.started":"2024-05-13T02:53:53.476942Z","shell.execute_reply":"2024-05-13T02:53:54.770865Z"},"trusted":true},"execution_count":723,"outputs":[]},{"cell_type":"code","source":"## correlation Matrix\n\ncorr = data.corr()\nplt.figure(figsize = (10,6))\nsns.heatmap(corr, annot = True)","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:54.773973Z","iopub.execute_input":"2024-05-13T02:53:54.775055Z","iopub.status.idle":"2024-05-13T02:53:55.954289Z","shell.execute_reply.started":"2024-05-13T02:53:54.775016Z","shell.execute_reply":"2024-05-13T02:53:55.952855Z"},"trusted":true},"execution_count":724,"outputs":[{"execution_count":724,"output_type":"execute_result","data":{"text/plain":"<Axes: >"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x600 with 2 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"print(X_train.shape)\nprint((np.array(y_train) == 1).sum())","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:55.956846Z","iopub.execute_input":"2024-05-13T02:53:55.957322Z","iopub.status.idle":"2024-05-13T02:53:55.971202Z","shell.execute_reply.started":"2024-05-13T02:53:55.957284Z","shell.execute_reply":"2024-05-13T02:53:55.969146Z"},"trusted":true},"execution_count":725,"outputs":[{"name":"stdout","text":"(1048723, 7)\n21573\n","output_type":"stream"}]},{"cell_type":"markdown","source":"**Model Training**","metadata":{}},{"cell_type":"code","source":"rfc=RandomForestClassifier(n_estimators = 100, n_jobs = -1, random_state = 42)\nlgbm = LGBMClassifier(boosting_type = 'gbdt',objective = 'binary', random_state = 8888)\nxgbr = xgb.XGBClassifier(max_depth = 3, n_jobs = -1, random_state = 42, learning_rate = 0.1)\nlogreg = LogisticRegression(solver = 'liblinear', random_state = 42)","metadata":{"id":"Rce4aFkIUS_q","execution":{"iopub.status.busy":"2024-05-13T02:53:55.972999Z","iopub.execute_input":"2024-05-13T02:53:55.973440Z","iopub.status.idle":"2024-05-13T02:53:55.982831Z","shell.execute_reply.started":"2024-05-13T02:53:55.973404Z","shell.execute_reply":"2024-05-13T02:53:55.981498Z"},"trusted":true},"execution_count":726,"outputs":[]},{"cell_type":"code","source":"rfc.fit(X_train, y_train)","metadata":{"execution":{"iopub.status.busy":"2024-05-13T02:53:55.984551Z","iopub.execute_input":"2024-05-13T02:53:55.984950Z","iopub.status.idle":"2024-05-13T02:59:50.714041Z","shell.execute_reply.started":"2024-05-13T02:53:55.984917Z","shell.execute_reply":"2024-05-13T02:59:50.712495Z"},"trusted":true},"execution_count":727,"outputs":[{"execution_count":727,"output_type":"execute_result","data":{"text/plain":"RandomForestClassifier(n_jobs=-1, random_state=42)","text/html":"<style>#sk-container-id-28 {color: black;background-color: white;}#sk-container-id-28 pre{padding: 0;}#sk-container-id-28 div.sk-toggleable {background-color: white;}#sk-container-id-28 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-28 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-28 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-28 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-28 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-28 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-28 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-28 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-28 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-28 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-28 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-28 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-28 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-28 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-28 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-28 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-28 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-28 div.sk-item {position: relative;z-index: 1;}#sk-container-id-28 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-28 div.sk-item::before, #sk-container-id-28 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-28 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-28 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-28 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-28 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-28 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-28 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-28 div.sk-label-container {text-align: center;}#sk-container-id-28 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-28 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-28\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestClassifier(n_jobs=-1, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-28\" type=\"checkbox\" checked><label for=\"sk-estimator-id-28\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestClassifier</label><div class=\"sk-toggleable__content\"><pre>RandomForestClassifier(n_jobs=-1, random_state=42)</pre></div></div></div></div></div>"},"metadata":{}}]},{"cell_type":"code","source":"## FineTune lgbm\n\nlgbm.fit(X_train, y_train)","metadata":{"id":"VotwTua1WupC","execution":{"iopub.status.busy":"2024-05-13T02:59:50.715911Z","iopub.execute_input":"2024-05-13T02:59:50.716318Z","iopub.status.idle":"2024-05-13T03:00:04.807312Z","shell.execute_reply.started":"2024-05-13T02:59:50.716284Z","shell.execute_reply":"2024-05-13T03:00:04.805834Z"},"trusted":true},"execution_count":728,"outputs":[{"name":"stdout","text":"[LightGBM] [Info] Number of positive: 21573, number of negative: 1027150\n[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.227945 seconds.\nYou can set `force_col_wise=true` to remove the overhead.\n[LightGBM] [Info] Total Bins 800\n[LightGBM] [Info] Number of data points in the train set: 1048723, number of used features: 7\n[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.020571 -> initscore=-3.863101\n[LightGBM] [Info] Start training from score -3.863101\n","output_type":"stream"},{"execution_count":728,"output_type":"execute_result","data":{"text/plain":"LGBMClassifier(objective='binary', random_state=8888)","text/html":"<style>#sk-container-id-29 {color: black;background-color: white;}#sk-container-id-29 pre{padding: 0;}#sk-container-id-29 div.sk-toggleable {background-color: white;}#sk-container-id-29 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-29 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-29 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-29 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-29 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-29 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-29 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-29 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-29 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-29 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-29 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-29 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-29 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-29 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-29 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-29 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-29 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-29 div.sk-item {position: relative;z-index: 1;}#sk-container-id-29 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-29 div.sk-item::before, #sk-container-id-29 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-29 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-29 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-29 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-29 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-29 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-29 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-29 div.sk-label-container {text-align: center;}#sk-container-id-29 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-29 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-29\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LGBMClassifier(objective=&#x27;binary&#x27;, random_state=8888)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-29\" type=\"checkbox\" checked><label for=\"sk-estimator-id-29\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LGBMClassifier</label><div class=\"sk-toggleable__content\"><pre>LGBMClassifier(objective=&#x27;binary&#x27;, random_state=8888)</pre></div></div></div></div></div>"},"metadata":{}}]},{"cell_type":"code","source":"xgbr.fit(X_train, y_train)","metadata":{"id":"7_wMmliCWJ32","execution":{"iopub.status.busy":"2024-05-13T03:00:04.808550Z","iopub.execute_input":"2024-05-13T03:00:04.808931Z","iopub.status.idle":"2024-05-13T03:00:14.537771Z","shell.execute_reply.started":"2024-05-13T03:00:04.808899Z","shell.execute_reply":"2024-05-13T03:00:14.536114Z"},"trusted":true},"execution_count":729,"outputs":[{"execution_count":729,"output_type":"execute_result","data":{"text/plain":"XGBClassifier(base_score=None, booster=None, callbacks=None,\n              colsample_bylevel=None, colsample_bynode=None,\n              colsample_bytree=None, device=None, early_stopping_rounds=None,\n              enable_categorical=False, eval_metric=None, feature_types=None,\n              gamma=None, grow_policy=None, importance_type=None,\n              interaction_constraints=None, learning_rate=0.1, max_bin=None,\n              max_cat_threshold=None, max_cat_to_onehot=None,\n              max_delta_step=None, max_depth=3, max_leaves=None,\n              min_child_weight=None, missing=nan, monotone_constraints=None,\n              multi_strategy=None, n_estimators=None, n_jobs=-1,\n              num_parallel_tree=None, random_state=42, ...)","text/html":"<style>#sk-container-id-30 {color: black;background-color: white;}#sk-container-id-30 pre{padding: 0;}#sk-container-id-30 div.sk-toggleable {background-color: white;}#sk-container-id-30 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-30 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-30 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-30 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-30 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-30 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-30 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-30 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-30 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-30 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-30 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-30 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-30 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-30 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-30 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-30 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-30 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-30 div.sk-item {position: relative;z-index: 1;}#sk-container-id-30 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-30 div.sk-item::before, #sk-container-id-30 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-30 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-30 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-30 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-30 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-30 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-30 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-30 div.sk-label-container {text-align: center;}#sk-container-id-30 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-30 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-30\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,\n              colsample_bylevel=None, colsample_bynode=None,\n              colsample_bytree=None, device=None, early_stopping_rounds=None,\n              enable_categorical=False, eval_metric=None, feature_types=None,\n              gamma=None, grow_policy=None, importance_type=None,\n              interaction_constraints=None, learning_rate=0.1, max_bin=None,\n              max_cat_threshold=None, max_cat_to_onehot=None,\n              max_delta_step=None, max_depth=3, max_leaves=None,\n              min_child_weight=None, missing=nan, monotone_constraints=None,\n              multi_strategy=None, n_estimators=None, n_jobs=-1,\n              num_parallel_tree=None, random_state=42, ...)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-30\" type=\"checkbox\" checked><label for=\"sk-estimator-id-30\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBClassifier</label><div class=\"sk-toggleable__content\"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,\n              colsample_bylevel=None, colsample_bynode=None,\n              colsample_bytree=None, device=None, early_stopping_rounds=None,\n              enable_categorical=False, eval_metric=None, feature_types=None,\n              gamma=None, grow_policy=None, importance_type=None,\n              interaction_constraints=None, learning_rate=0.1, max_bin=None,\n              max_cat_threshold=None, max_cat_to_onehot=None,\n              max_delta_step=None, max_depth=3, max_leaves=None,\n              min_child_weight=None, missing=nan, monotone_constraints=None,\n              multi_strategy=None, n_estimators=None, n_jobs=-1,\n              num_parallel_tree=None, random_state=42, ...)</pre></div></div></div></div></div>"},"metadata":{}}]},{"cell_type":"code","source":"logreg.fit(X_train, y_train)\n\nclassifiers = []\nclassifiers.append(rfc)\nclassifiers.append(lgbm)\nclassifiers.append(xgbr)\nclassifiers.append(logreg)","metadata":{"id":"O9EfuPKYWzVF","execution":{"iopub.status.busy":"2024-05-13T03:00:14.539855Z","iopub.execute_input":"2024-05-13T03:00:14.540323Z","iopub.status.idle":"2024-05-13T03:00:17.085894Z","shell.execute_reply.started":"2024-05-13T03:00:14.540288Z","shell.execute_reply":"2024-05-13T03:00:17.084593Z"},"trusted":true},"execution_count":730,"outputs":[]},{"cell_type":"code","source":"accuracy_list = []\nauc_list = []\n\nfor classifier in classifiers:\n    y_pred = classifier.predict(X_test)\n    y_pred_proba = classifier.predict_proba(X_test)[:,1]\n    accuracy_list.append(accuracy_score(y_test, y_pred))\n    auc_list.append(roc_auc_score(y_test, y_pred_proba))\n\naccuracy_dict = {}\nauc_dict = {}\nfor i in range(4):\n    key=['Random Forest', 'Light GBM', 'XGBoost','LR'][i]\n    accuracy_dict[key] = accuracy_list[i]\n    auc_dict[key] = auc_list[i]\n\naccuracy_dict_sorted = dict(sorted(accuracy_dict.items(), key = lambda item: item[1]))\nauc_dict_sorted = dict(sorted(auc_dict.items(), key = lambda item: item[1]))","metadata":{"id":"YwbbHBlbUg5r","execution":{"iopub.status.busy":"2024-05-13T03:00:17.087402Z","iopub.execute_input":"2024-05-13T03:00:17.087744Z","iopub.status.idle":"2024-05-13T03:00:44.773460Z","shell.execute_reply.started":"2024-05-13T03:00:17.087714Z","shell.execute_reply":"2024-05-13T03:00:44.772150Z"},"trusted":true},"execution_count":731,"outputs":[]},{"cell_type":"code","source":"def px_bar(x,y,text,title,color,color_discrete_sequence):\n    return px.bar(x = x, y = y, text = text, title = title, color = color, color_discrete_sequence=color_discrete_sequence)","metadata":{"id":"p9XYfE-QUn1n","execution":{"iopub.status.busy":"2024-05-13T03:00:44.777758Z","iopub.execute_input":"2024-05-13T03:00:44.778166Z","iopub.status.idle":"2024-05-13T03:00:44.785193Z","shell.execute_reply.started":"2024-05-13T03:00:44.778135Z","shell.execute_reply":"2024-05-13T03:00:44.784013Z"},"trusted":true},"execution_count":732,"outputs":[]},{"cell_type":"code","source":"fig = px_bar(list(accuracy_dict_sorted.keys()), list(accuracy_dict_sorted.values()), np.round(list(accuracy_dict_sorted.values()),3), 'Accuracy score of each classifiers', list(accuracy_dict_sorted.keys()), px.colors.sequential.matter)\nfor idx in [2,3]:\n    fig.data[idx].marker.line.width = 3\n    fig.data[idx].marker.line.color = \"black\"\nfig.show()","metadata":{"id":"x6heUEPhUoWb","execution":{"iopub.status.busy":"2024-05-13T03:00:44.786303Z","iopub.execute_input":"2024-05-13T03:00:44.786615Z","iopub.status.idle":"2024-05-13T03:00:44.894583Z","shell.execute_reply.started":"2024-05-13T03:00:44.786589Z","shell.execute_reply":"2024-05-13T03:00:44.893149Z"},"trusted":true},"execution_count":733,"outputs":[{"output_type":"display_data","data":{"text/html":"<div>                            <div id=\"d25549d0-6736-4f1b-8b82-b87679ef099c\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"d25549d0-6736-4f1b-8b82-b87679ef099c\")) {                    Plotly.newPlot(                        \"d25549d0-6736-4f1b-8b82-b87679ef099c\",                        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    </div>"},"metadata":{}}]},{"cell_type":"code","source":"rfc_pred = rfc.predict(X_test)\nrfc_pred_proba = rfc.predict_proba(X_test)[:,1]\n\nlgbm_pred = lgbm.predict(X_test)\nlgbm_pred_proba = rfc.predict_proba(X_test)[:,1]\n\nxgbr_pred = xgbr.predict(X_test)\nxgbr_pred_proba = rfc.predict_proba(X_test)[:,1]\n\nlogreg_pred = logreg.predict(X_test)\nlogreg_pred_proba = rfc.predict_proba(X_test)[:,1]","metadata":{"id":"TB4q9pB1UyRA","execution":{"iopub.status.busy":"2024-05-13T03:00:45.008705Z","iopub.execute_input":"2024-05-13T03:00:45.009682Z","iopub.status.idle":"2024-05-13T03:01:42.536613Z","shell.execute_reply.started":"2024-05-13T03:00:45.009633Z","shell.execute_reply":"2024-05-13T03:01:42.535083Z"},"trusted":true},"execution_count":735,"outputs":[]},{"cell_type":"code","source":"print(classification_report(y_test, rfc_pred, target_names=['Not Fraud','Fraud']))\nprint(pd.crosstab(y_test, rfc_pred))","metadata":{"id":"kFepoMVMU3u3","execution":{"iopub.status.busy":"2024-05-13T03:01:42.539148Z","iopub.execute_input":"2024-05-13T03:01:42.539697Z","iopub.status.idle":"2024-05-13T03:01:43.361631Z","shell.execute_reply.started":"2024-05-13T03:01:42.539641Z","shell.execute_reply":"2024-05-13T03:01:43.360297Z"},"trusted":true},"execution_count":736,"outputs":[{"name":"stdout","text":"              precision    recall  f1-score   support\n\n   Not Fraud       0.99      1.00      0.99    440208\n       Fraud       0.97      0.32      0.48      9246\n\n    accuracy                           0.99    449454\n   macro avg       0.98      0.66      0.74    449454\nweighted avg       0.99      0.99      0.98    449454\n\ncol_0       0     1\nLabel              \n0      440104   104\n1        6283  2963\n","output_type":"stream"}]},{"cell_type":"code","source":"print(classification_report(y_test, lgbm_pred, target_names=['Not Fraud','Fraud']))\nprint(pd.crosstab(y_test, lgbm_pred))","metadata":{"id":"zmOwHnzqW8--","execution":{"iopub.status.busy":"2024-05-13T03:01:43.363576Z","iopub.execute_input":"2024-05-13T03:01:43.363929Z","iopub.status.idle":"2024-05-13T03:01:44.099498Z","shell.execute_reply.started":"2024-05-13T03:01:43.363899Z","shell.execute_reply":"2024-05-13T03:01:44.097842Z"},"trusted":true},"execution_count":737,"outputs":[{"name":"stdout","text":"              precision    recall  f1-score   support\n\n   Not Fraud       0.99      1.00      0.99    440208\n       Fraud       1.00      0.32      0.48      9246\n\n    accuracy                           0.99    449454\n   macro avg       0.99      0.66      0.74    449454\nweighted avg       0.99      0.99      0.98    449454\n\ncol_0       0     1\nLabel              \n0      440208     0\n1        6287  2959\n","output_type":"stream"}]},{"cell_type":"code","source":"print(classification_report(y_test, xgbr_pred, target_names=['Not Fraud','Fraud']))\nprint(pd.crosstab(y_test, xgbr_pred))","metadata":{"id":"hOad8P85XClR","execution":{"iopub.status.busy":"2024-05-13T03:01:44.101456Z","iopub.execute_input":"2024-05-13T03:01:44.101920Z","iopub.status.idle":"2024-05-13T03:01:44.876645Z","shell.execute_reply.started":"2024-05-13T03:01:44.101878Z","shell.execute_reply":"2024-05-13T03:01:44.875749Z"},"trusted":true},"execution_count":738,"outputs":[{"name":"stdout","text":"              precision    recall  f1-score   support\n\n   Not Fraud       0.98      1.00      0.99    440208\n       Fraud       0.98      0.19      0.31      9246\n\n    accuracy                           0.98    449454\n   macro avg       0.98      0.59      0.65    449454\nweighted avg       0.98      0.98      0.98    449454\n\ncol_0       0     1\nLabel              \n0      440176    32\n1        7532  1714\n","output_type":"stream"}]},{"cell_type":"code","source":"print(classification_report(y_test, logreg_pred, target_names=['Not Fraud','Fraud']))","metadata":{"id":"1dtgcpXLXFL9","execution":{"iopub.status.busy":"2024-05-13T03:01:44.878051Z","iopub.execute_input":"2024-05-13T03:01:44.879475Z","iopub.status.idle":"2024-05-13T03:01:45.634678Z","shell.execute_reply.started":"2024-05-13T03:01:44.879436Z","shell.execute_reply":"2024-05-13T03:01:45.633064Z"},"trusted":true},"execution_count":739,"outputs":[{"name":"stdout","text":"              precision    recall  f1-score   support\n\n   Not Fraud       0.98      1.00      0.99    440208\n       Fraud       0.87      0.02      0.03      9246\n\n    accuracy                           0.98    449454\n   macro avg       0.93      0.51      0.51    449454\nweighted avg       0.98      0.98      0.97    449454\n\n","output_type":"stream"}]},{"cell_type":"code","source":"fpr, tpr, temp = roc_curve(y_test, rfc_pred_proba)\nauc = round(roc_auc_score(y_test, rfc_pred_proba),3)\nplt.figure(figsize=(15,7))\nplt.plot(fpr,tpr,label='Random Forest Classifier, AUC='+str(auc),linestyle='solid',color='#800000')\nplt.plot([0, 1], [0, 1], color = 'g')\nplt.title('ROC Curve')\nplt.legend(loc='upper right')","metadata":{"id":"LHlOTCfwVVx1","execution":{"iopub.status.busy":"2024-05-13T03:01:45.636592Z","iopub.execute_input":"2024-05-13T03:01:45.637451Z","iopub.status.idle":"2024-05-13T03:01:46.193339Z","shell.execute_reply.started":"2024-05-13T03:01:45.637401Z","shell.execute_reply":"2024-05-13T03:01:46.191850Z"},"trusted":true},"execution_count":740,"outputs":[{"execution_count":740,"output_type":"execute_result","data":{"text/plain":"<matplotlib.legend.Legend at 0x7fb8e32dce50>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 1500x700 with 1 Axes>","image/png":"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"},"metadata":{}}]}]}