PatternMining_AssociationRules.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "39d3fa53-82de-4043-9049-b25206c314b7",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "c6bfc72a-87c7-4062-a2b5-3b16905abd1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(r\"Seismic_Bumps/seismic-bumps.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "b1b05226-e767-4ccf-9d31-105bdb1331ce",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>seismic</th>\n",
       "      <th>seismoacoustic</th>\n",
       "      <th>shift</th>\n",
       "      <th>genergy</th>\n",
       "      <th>gpuls</th>\n",
       "      <th>gdenergy</th>\n",
       "      <th>gdpuls</th>\n",
       "      <th>hazard</th>\n",
       "      <th>nbumps</th>\n",
       "      <th>nbumps2</th>\n",
       "      <th>nbumps3</th>\n",
       "      <th>nbumps4</th>\n",
       "      <th>nbumps5</th>\n",
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       "      <th>4</th>\n",
       "      <td>a</td>\n",
       "      <td>a</td>\n",
       "      <td>N</td>\n",
       "      <td>12640</td>\n",
       "      <td>57</td>\n",
       "      <td>-63</td>\n",
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      ],
      "text/plain": [
       "  seismic seismoacoustic shift  genergy  gpuls  gdenergy  gdpuls hazard  \\\n",
       "0       a              a     N    15180     48       -72     -72      a   \n",
       "1       a              a     N    14720     33       -70     -79      a   \n",
       "2       a              a     N     8050     30       -81     -78      a   \n",
       "3       a              a     N    28820    171       -23      40      a   \n",
       "4       a              a     N    12640     57       -63     -52      a   \n",
       "\n",
       "   nbumps  nbumps2  nbumps3  nbumps4  nbumps5  energy  maxenergy  class  \n",
       "0       0        0        0        0        0       0          0      0  \n",
       "1       1        0        1        0        0    2000       2000      0  \n",
       "2       0        0        0        0        0       0          0      0  \n",
       "3       1        0        1        0        0    3000       3000      0  \n",
       "4       0        0        0        0        0       0          0      0  "
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     "execution_count": 131,
     "metadata": {},
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   ],
   "source": [
    "df.head()"
   ]
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  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "7d195594-4f11-42a2-aa13-8c194f6a6502",
   "metadata": {},
   "outputs": [],
   "source": [
    "# we keep shift, genergy, gpuls, nbumps4, energy, seismoacoustic, class \n",
    "column2drop = ['gdenergy', 'gdpuls', 'nbumps', 'nbumps2', 'nbumps3', 'seismic', 'maxenergy', 'hazard'] \n",
    "df.drop(column2drop, axis=1, inplace=True)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 133,
   "id": "d75caf0d-afdb-44cd-923c-0339962f1312",
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      "text/plain": [
       "     seismoacoustic shift  genergy  gpuls  nbumps4  nbumps5  energy  class\n",
       "0                 a     N    15180     48        0        0       0      0\n",
       "1                 a     N    14720     33        0        0    2000      0\n",
       "2                 a     N     8050     30        0        0       0      0\n",
       "3                 a     N    28820    171        0        0    3000      0\n",
       "4                 a     N    12640     57        0        0       0      0\n",
       "...             ...   ...      ...    ...      ...      ...     ...    ...\n",
       "2558              a     W    81410    785        0        0       0      0\n",
       "2559              a     W    42110    555        0        0       0      0\n",
       "2560              a     W    26960    540        0        0       0      0\n",
       "2561              a     W    16130    322        0        0       0      0\n",
       "2562              a     W    12750    235        0        0       0      0\n",
       "\n",
       "[2563 rows x 8 columns]"
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     "execution_count": 133,
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    "df"
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   "cell_type": "code",
   "execution_count": 134,
   "id": "baee00a4-cfdb-4473-8ed4-d98b384fa107",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['GenergyBin'] = pd.qcut(df['genergy'], 4)\n",
    "df['GpulsBin'] = pd.qcut(df['gpuls'], 4)\n",
    "#df['EnergyBin'] = pd.qcut(df['energy'], 4)\n",
    "\n",
    "df.drop(['genergy', 'gpuls'], axis=1, inplace=True)\n"
   ]
  },
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   "execution_count": 135,
   "id": "61e0385e-f43e-40fb-b90d-0c9a48c0b476",
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      ],
      "text/plain": [
       "     seismoacoustic shift  nbumps4  nbumps5  energy  class  \\\n",
       "0                 a     N        0        0       0      0   \n",
       "1                 a     N        0        0    2000      0   \n",
       "2                 a     N        0        0       0      0   \n",
       "3                 a     N        0        0    3000      0   \n",
       "4                 a     N        0        0       0      0   \n",
       "...             ...   ...      ...      ...     ...    ...   \n",
       "2558              a     W        0        0       0      0   \n",
       "2559              a     W        0        0       0      0   \n",
       "2560              a     W        0        0       0      0   \n",
       "2561              a     W        0        0       0      0   \n",
       "2562              a     W        0        0       0      0   \n",
       "\n",
       "                GenergyBin         GpulsBin  \n",
       "0       (11560.0, 25390.0]   (1.999, 189.0]  \n",
       "1       (11560.0, 25390.0]   (1.999, 189.0]  \n",
       "2        (99.999, 11560.0]   (1.999, 189.0]  \n",
       "3       (25390.0, 52010.0]   (1.999, 189.0]  \n",
       "4       (11560.0, 25390.0]   (1.999, 189.0]  \n",
       "...                    ...              ...  \n",
       "2558  (52010.0, 1766860.0]  (661.5, 3915.0]  \n",
       "2559    (25390.0, 52010.0]   (376.0, 661.5]  \n",
       "2560    (25390.0, 52010.0]   (376.0, 661.5]  \n",
       "2561    (11560.0, 25390.0]   (189.0, 376.0]  \n",
       "2562    (11560.0, 25390.0]   (189.0, 376.0]  \n",
       "\n",
       "[2563 rows x 8 columns]"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "43958243-cd46-471f-889c-999d70e38f7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['GenergyBin'] = df['GenergyBin'].astype(str) + '_Genergy'\n",
    "df['GpulsBin'] = df['GpulsBin'].astype(str) + '_Gpuls'\n",
    "df['nbumps4'] = df['nbumps4'].astype(str) + '_Nbumps4'\n",
    "df['nbumps5'] = df['nbumps5'].astype(str) + '_Nbumps5'\n",
    "df['energy'] = df['energy'].astype(str) + '_Energy'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "d3053b1f-cd49-4fcb-a158-7e5b9cd2f11f",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>seismoacoustic</th>\n",
       "      <th>shift</th>\n",
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       "      <td>0_Nbumps5</td>\n",
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       "      <td>0_Nbumps5</td>\n",
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       "      <td>0</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
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       "      <th>4</th>\n",
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       "      <td>N</td>\n",
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       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
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       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
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       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>0</td>\n",
       "      <td>(52010.0, 1766860.0]_Genergy</td>\n",
       "      <td>(661.5, 3915.0]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2559</th>\n",
       "      <td>a</td>\n",
       "      <td>W</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>0</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
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       "      <th>2560</th>\n",
       "      <td>a</td>\n",
       "      <td>W</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>0</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
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       "      <td>a</td>\n",
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       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>0</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
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       "      <td>a</td>\n",
       "      <td>W</td>\n",
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       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>0</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>2563 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     seismoacoustic shift    nbumps4    nbumps5       energy  class  \\\n",
       "0                 a     N  0_Nbumps4  0_Nbumps5     0_Energy      0   \n",
       "1                 a     N  0_Nbumps4  0_Nbumps5  2000_Energy      0   \n",
       "2                 a     N  0_Nbumps4  0_Nbumps5     0_Energy      0   \n",
       "3                 a     N  0_Nbumps4  0_Nbumps5  3000_Energy      0   \n",
       "4                 a     N  0_Nbumps4  0_Nbumps5     0_Energy      0   \n",
       "...             ...   ...        ...        ...          ...    ...   \n",
       "2558              a     W  0_Nbumps4  0_Nbumps5     0_Energy      0   \n",
       "2559              a     W  0_Nbumps4  0_Nbumps5     0_Energy      0   \n",
       "2560              a     W  0_Nbumps4  0_Nbumps5     0_Energy      0   \n",
       "2561              a     W  0_Nbumps4  0_Nbumps5     0_Energy      0   \n",
       "2562              a     W  0_Nbumps4  0_Nbumps5     0_Energy      0   \n",
       "\n",
       "                        GenergyBin               GpulsBin  \n",
       "0       (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "1       (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "2        (99.999, 11560.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "3       (25390.0, 52010.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "4       (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "...                            ...                    ...  \n",
       "2558  (52010.0, 1766860.0]_Genergy  (661.5, 3915.0]_Gpuls  \n",
       "2559    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls  \n",
       "2560    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls  \n",
       "2561    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls  \n",
       "2562    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls  \n",
       "\n",
       "[2563 rows x 8 columns]"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "4d337a05-c566-427c-a501-0f983f14c28d",
   "metadata": {},
   "outputs": [],
   "source": [
    "class_dict = {0: 'Non_Hazardous', 1: 'Hazardous'}\n",
    "seism_dict = {'a': 'Lack_of_hazard', 'b': 'Low_hazard', 'c': 'High_hazard', 'd': 'Danger_state'}\n",
    "shift_dict = {'N': 'Preparation_shift', 'W': 'Coal_getting_shift'}\n",
    "df['class'] = df['class'].map(class_dict)\n",
    "df['seismoacoustic'] = df['seismoacoustic'].map(seism_dict)\n",
    "df['shift'] = df['shift'].map(shift_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "7e2dc84c-cbb1-42de-8263-aeda6bf13e3d",
   "metadata": {},
   "outputs": [
    {
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       "      <th>2558</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(52010.0, 1766860.0]_Genergy</td>\n",
       "      <td>(661.5, 3915.0]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2559</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2560</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2561</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2562</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
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       "</table>\n",
       "<p>2563 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      seismoacoustic               shift    nbumps4    nbumps5       energy  \\\n",
       "0     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "1     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  2000_Energy   \n",
       "2     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "3     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  3000_Energy   \n",
       "4     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "...              ...                 ...        ...        ...          ...   \n",
       "2558  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2559  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2560  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2561  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2562  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "\n",
       "              class                    GenergyBin               GpulsBin  \n",
       "0     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "1     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "2     Non_Hazardous     (99.999, 11560.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "3     Non_Hazardous    (25390.0, 52010.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "4     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "...             ...                           ...                    ...  \n",
       "2558  Non_Hazardous  (52010.0, 1766860.0]_Genergy  (661.5, 3915.0]_Gpuls  \n",
       "2559  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls  \n",
       "2560  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls  \n",
       "2561  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls  \n",
       "2562  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls  \n",
       "\n",
       "[2563 rows x 8 columns]"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "880e041f-5487-4a17-aacf-f48868c3b573",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Lack_of_hazard',\n",
       " 'Preparation_shift',\n",
       " '0_Nbumps4',\n",
       " '0_Nbumps5',\n",
       " '0_Energy',\n",
       " 'Non_Hazardous',\n",
       " '(11560.0, 25390.0]_Genergy',\n",
       " '(1.999, 189.0]_Gpuls']"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = df.values.tolist()\n",
    "X[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "6cd9909f-e329-4d5d-ae3f-5dddf43812f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "from fim import apriori"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "e4f2853d-3e49-4c0e-a8c5-8f53c2d8afd1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Support: 85 Target: a\n",
      "Frequent itemsets: 7\n",
      "\n",
      "Support: 85 Target: c\n",
      "Frequent itemsets: 5\n",
      "\n",
      "Support: 85 Target: m\n",
      "Frequent itemsets: 1\n",
      "\n",
      "Support: 50 Target: a\n",
      "Frequent itemsets: 31\n",
      "\n",
      "Support: 50 Target: c\n",
      "Frequent itemsets: 17\n",
      "\n",
      "Support: 50 Target: m\n",
      "Frequent itemsets: 3\n",
      "\n",
      "Support: 30 Target: a\n",
      "Frequent itemsets: 67\n",
      "\n",
      "Support: 30 Target: c\n",
      "Frequent itemsets: 34\n",
      "\n",
      "Support: 30 Target: m\n",
      "Frequent itemsets: 5\n",
      "\n",
      "Support: 20 Target: a\n",
      "Frequent itemsets: 195\n",
      "\n",
      "Support: 20 Target: c\n",
      "Frequent itemsets: 99\n",
      "\n",
      "Support: 20 Target: m\n",
      "Frequent itemsets: 22\n",
      "\n",
      "Support: 10 Target: a\n",
      "Frequent itemsets: 607\n",
      "\n",
      "Support: 10 Target: c\n",
      "Frequent itemsets: 268\n",
      "\n",
      "Support: 10 Target: m\n",
      "Frequent itemsets: 30\n",
      "\n",
      "Support: 5 Target: a\n",
      "Frequent itemsets: 1095\n",
      "\n",
      "Support: 5 Target: c\n",
      "Frequent itemsets: 468\n",
      "\n",
      "Support: 5 Target: m\n",
      "Frequent itemsets: 48\n",
      "\n",
      "Support: 4 Target: a\n",
      "Frequent itemsets: 1263\n",
      "\n",
      "Support: 4 Target: c\n",
      "Frequent itemsets: 528\n",
      "\n",
      "Support: 4 Target: m\n",
      "Frequent itemsets: 41\n",
      "\n",
      "Support: 3 Target: a\n",
      "Frequent itemsets: 1586\n",
      "\n",
      "Support: 3 Target: c\n",
      "Frequent itemsets: 651\n",
      "\n",
      "Support: 3 Target: m\n",
      "Frequent itemsets: 50\n",
      "\n",
      "Support: 2 Target: a\n",
      "Frequent itemsets: 1914\n",
      "\n",
      "Support: 2 Target: c\n",
      "Frequent itemsets: 776\n",
      "\n",
      "Support: 2 Target: m\n",
      "Frequent itemsets: 57\n",
      "\n",
      "Support: 0.9 Target: a\n",
      "Frequent itemsets: 2957\n",
      "\n",
      "Support: 0.9 Target: c\n",
      "Frequent itemsets: 1069\n",
      "\n",
      "Support: 0.9 Target: m\n",
      "Frequent itemsets: 92\n",
      "\n",
      "Support: 0.8 Target: a\n",
      "Frequent itemsets: 3145\n",
      "\n",
      "Support: 0.8 Target: c\n",
      "Frequent itemsets: 1117\n",
      "\n",
      "Support: 0.8 Target: m\n",
      "Frequent itemsets: 103\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Frequent itemsets (prova)\n",
    "supp = [85, 50, 30, 20, 10, 5, 4, 3, 2, 0.9, 0.8]\n",
    "target = [\"a\", \"c\", \"m\"]\n",
    "\n",
    "for s in supp:\n",
    "    for t in target:\n",
    "        itemsets = apriori(X, target=t, supp=s, report=\"s\")\n",
    "        print(\"Support:\", s, \"Target:\",t)\n",
    "        print(\"Frequent itemsets:\", len(itemsets))\n",
    "        print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "a7ec08f6-ba55-4967-8cdf-550de9d77552",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(('(376.0, 661.5]_Gpuls', 'Coal_getting_shift', '0_Nbumps5'), 541, 21.10807647288334), (('(376.0, 661.5]_Gpuls', 'Non_Hazardous', '0_Nbumps5'), 599, 23.371049551307063), (('(376.0, 661.5]_Gpuls', 'Non_Hazardous', '0_Nbumps4', '0_Nbumps5'), 572, 22.317596566523605), (('(376.0, 661.5]_Gpuls', 'Non_Hazardous', '0_Nbumps4'), 572, 22.317596566523605), (('(376.0, 661.5]_Gpuls', '0_Nbumps4', '0_Nbumps5'), 608, 23.72220054623488), (('(25390.0, 52010.0]_Genergy', 'Coal_getting_shift', '0_Nbumps5'), 546, 21.30316035895435)]\n"
     ]
    }
   ],
   "source": [
    "#cerco i frequent itemsets -- altro metodo\n",
    "# report indica le metriche di valutazione dell'association rule -> S = support, C = confidence, l= lift value of a rule (confidence/prior)\n",
    "# supp indica il support minimo (il default è 10 quindi non serve metterlo)\n",
    "# zmin indica il numero minimo di item nell'itemset, zmax il massimo\n",
    "# target indica il tipo di itemset che stiamo carcando -> r = association rule\n",
    "# conf indica il minimum confidence \n",
    "itemsets = apriori(X, supp=20, zmin=3, zmax=6, target='s', conf=20, report='aS') \n",
    "print(itemsets[:6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "e82a5bcc-b0c6-4e16-b193-8569e45156e2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(('Non_Hazardous', '0_Nbumps4', '0_Nbumps5'), 2261, 88.21693328131096)\n",
      "(('Coal_getting_shift', '0_Nbumps4', '0_Nbumps5'), 1501, 58.56418259851737)\n",
      "(('Coal_getting_shift', 'Non_Hazardous', '0_Nbumps5'), 1493, 58.25204838080374)\n",
      "(('Lack_of_hazard', '0_Nbumps4', '0_Nbumps5'), 1476, 57.5887631681623)\n",
      "(('Lack_of_hazard', 'Non_Hazardous', '0_Nbumps5'), 1467, 57.23761217323449)\n",
      "(('0_Energy', '0_Nbumps4', '0_Nbumps5'), 1462, 57.042528287163485)\n",
      "(('0_Energy', 'Non_Hazardous', '0_Nbumps4', '0_Nbumps5'), 1422, 55.4818571985954)\n",
      "(('0_Energy', 'Non_Hazardous', '0_Nbumps4'), 1422, 55.4818571985954)\n",
      "(('0_Energy', 'Non_Hazardous', '0_Nbumps5'), 1422, 55.4818571985954)\n",
      "(('Lack_of_hazard', 'Non_Hazardous', '0_Nbumps4', '0_Nbumps5'), 1387, 54.11626999609832)\n",
      "(('Lack_of_hazard', 'Non_Hazardous', '0_Nbumps4'), 1387, 54.11626999609832)\n"
     ]
    }
   ],
   "source": [
    "itemsets.sort(key=lambda x: x[2],reverse=True) #ordina in base al support\n",
    "\n",
    "#for x in itemsets:\n",
    "for x in range(0, 11):\n",
    "#    if x[0]== '1_Nbumps4':\n",
    "        print(itemsets[x])\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "id": "7ebde763-6798-409e-8e15-f08e183a1520",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('Lack_of_hazard', ('0_Energy', 'Non_Hazardous', '0_Nbumps4', '0_Nbumps5'), 34.02262973078424, 61.32208157524614, 1.002350096156606), ('0_Energy', ('Lack_of_hazard', 'Non_Hazardous', '0_Nbumps4', '0_Nbumps5'), 34.02262973078424, 62.86950252343186, 1.1021514019668666), ('Lack_of_hazard', ('0_Energy', 'Non_Hazardous', '0_Nbumps4'), 34.02262973078424, 61.32208157524614, 1.002350096156606), ('0_Energy', ('Lack_of_hazard', 'Non_Hazardous', '0_Nbumps4'), 34.02262973078424, 62.86950252343186, 1.1021514019668666), ('Lack_of_hazard', ('0_Energy', 'Non_Hazardous', '0_Nbumps5'), 34.02262973078424, 61.32208157524614, 1.002350096156606), ('0_Energy', ('Lack_of_hazard', 'Non_Hazardous', '0_Nbumps5'), 34.02262973078424, 59.44103612815269, 1.042047712698053)]\n"
     ]
    }
   ],
   "source": [
    "itemsets = apriori(X, supp=50, zmin=3, zmax=6, target='r', conf=50, report='SCl') \n",
    "\n",
    "print(itemsets[:6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "id": "e1eac267-ac98-4896-899c-fab6f22a3f31",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Non_Hazardous', ('0_Energy', '0_Nbumps4', '0_Nbumps5'), 55.4818571985954, 97.2640218878249, 1.0417371002862315)\n",
      "('Non_Hazardous', ('0_Energy', '0_Nbumps4'), 55.4818571985954, 97.2640218878249, 1.0417371002862315)\n",
      "('Non_Hazardous', ('0_Energy', '0_Nbumps5'), 55.4818571985954, 97.2640218878249, 1.0417371002862315)\n",
      "('Non_Hazardous', ('Lack_of_hazard', '0_Nbumps4', '0_Nbumps5'), 54.11626999609832, 93.97018970189703, 1.0064588224235773)\n",
      "('Non_Hazardous', ('Lack_of_hazard', '0_Nbumps4'), 54.11626999609832, 93.97018970189703, 1.0064588224235773)\n",
      "('Non_Hazardous', ('0_Nbumps4', '0_Nbumps5'), 88.21693328131096, 93.8953488372093, 1.005657246426107)\n",
      "('Non_Hazardous', ('Lack_of_hazard', '0_Nbumps5'), 57.23761217323449, 93.55867346938776, 1.0020513167657368)\n",
      "('Non_Hazardous', ('Coal_getting_shift', '0_Nbumps4', '0_Nbumps5'), 53.41396800624268, 91.20586275816123, 0.9768517603391861)\n",
      "('Non_Hazardous', ('Coal_getting_shift', '0_Nbumps4'), 53.41396800624268, 91.14513981358189, 0.9762013929887605)\n",
      "('Non_Hazardous', ('Coal_getting_shift', '0_Nbumps5'), 58.25204838080374, 90.75987841945289, 0.9720750872923433)\n"
     ]
    }
   ],
   "source": [
    "itemsets.sort(key=lambda x: x[4],reverse=True) #ordina in base al support\n",
    "\n",
    "for x in itemsets:\n",
    "#for x in range(0, 11):\n",
    "    if x[0]== 'Non_Hazardous':\n",
    "        print(x)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "d23fe7a7-1d4d-43fb-8d14-03535adac6dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('1_Nbumps4', ('(52010.0, 1766860.0]_Genergy', '(661.5, 3915.0]_Gpuls', 'Lack_of_hazard', '0_Nbumps5'), 50, 1.9508388607101055, 18.796992481203006, 3.4167866474697384), ('1_Nbumps4', ('(52010.0, 1766860.0]_Genergy', '(661.5, 3915.0]_Gpuls', 'Lack_of_hazard'), 50, 1.9508388607101055, 18.796992481203006, 3.4167866474697384), ('1_Nbumps4', ('(52010.0, 1766860.0]_Genergy', '(661.5, 3915.0]_Gpuls', 'Coal_getting_shift', 'Non_Hazardous', '0_Nbumps5'), 63, 2.458056964494733, 18.421052631578945, 3.3484509145203436), ('1_Nbumps4', ('(52010.0, 1766860.0]_Genergy', '(661.5, 3915.0]_Gpuls', 'Coal_getting_shift', 'Non_Hazardous'), 63, 2.458056964494733, 18.421052631578945, 3.3484509145203436), ('1_Nbumps4', ('(52010.0, 1766860.0]_Genergy', '(661.5, 3915.0]_Gpuls', 'Coal_getting_shift', '0_Nbumps5'), 76, 2.96527506827936, 18.225419664268586, 3.312890113441162), ('1_Nbumps4', ('(52010.0, 1766860.0]_Genergy', '(661.5, 3915.0]_Gpuls', 'Coal_getting_shift'), 76, 2.96527506827936, 18.181818181818183, 3.3049645390070923)]\n"
     ]
    }
   ],
   "source": [
    "itemsets = apriori(X, supp=10, zmin=3, zmax=6, target='r', conf=18, report='aSCl') \n",
    "print(itemsets[:6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "6c197d0c-e8d7-406e-8b49-ec9077284cd1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Hazardous', ('(52010.0, 1766860.0]_Genergy', '(661.5, 3915.0]_Gpuls', 'Coal_getting_shift'), 76, 2.96527506827936, 18.181818181818183, 2.7411764705882353)\n",
      "('Hazardous', ('(52010.0, 1766860.0]_Genergy', '(661.5, 3915.0]_Gpuls', '0_Nbumps4'), 63, 2.458056964494733, 18.05157593123209, 2.721540535985168)\n",
      "('Hazardous', ('(52010.0, 1766860.0]_Genergy', '(661.5, 3915.0]_Gpuls', 'Coal_getting_shift', '0_Nbumps4'), 62, 2.419040187280531, 18.562874251497004, 2.7986262768580485)\n",
      "('Hazardous', ('(52010.0, 1766860.0]_Genergy', '(661.5, 3915.0]_Gpuls', 'Coal_getting_shift', '0_Nbumps4', '0_Nbumps5'), 61, 2.380023410066329, 18.31831831831832, 2.7617558735205794)\n",
      "('Hazardous', ('(52010.0, 1766860.0]_Genergy', '(661.5, 3915.0]_Gpuls', 'Lack_of_hazard', '0_Nbumps5'), 51, 1.9898556379243075, 19.172932330827066, 2.8906015037593984)\n",
      "('Hazardous', ('(52010.0, 1766860.0]_Genergy', '(661.5, 3915.0]_Gpuls', 'Lack_of_hazard'), 51, 1.9898556379243075, 19.172932330827066, 2.8906015037593984)\n"
     ]
    }
   ],
   "source": [
    "itemsets.sort(key=lambda x: x[3],reverse=True) #ordina in base al support\n",
    "\n",
    "for x in itemsets:\n",
    "#for x in range(0, 11):\n",
    "    if x[0]== 'Hazardous':\n",
    "        print(x)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "578d3cc3-f45b-4774-8697-401762f580ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "len_max_it = []\n",
    "len_cl_it = []\n",
    "for i in range(2, 20+1):\n",
    "    max_itemsets = apriori(X, target='m', supp=i, zmin=3)\n",
    "    cl_itemsets = apriori(X, target='c', supp=i, zmin=3)\n",
    "    len_max_it.append( len(max_itemsets)  )\n",
    "    len_cl_it.append( len(cl_itemsets) )\n",
    "    \n",
    "plt.plot(len_max_it, label='maximal')\n",
    "plt.plot(len_cl_it, label='closed')\n",
    "plt.legend(fontsize=20)\n",
    "plt.xticks(fontsize=20)\n",
    "plt.xlabel('%support', fontsize=15)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "81770696-ee2b-465b-b44d-3dc57f5574b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "filter_1 = []\n",
    "filter_2 = []\n",
    "for i in range(2, 20+1):\n",
    "    max_itemsets = apriori(X, target='m', supp=i, zmin=3)\n",
    "    \n",
    "    filter_1.append( len([item for item in max_itemsets if 'Non_Hazardous' in item[0]])  )\n",
    "    filter_2.append( len([item for item in max_itemsets if 'Hazardous' in item[0]]) )\n",
    "    \n",
    "plt.plot(filter_1, label='w/ Non_Hazardous')\n",
    "plt.plot(filter_2, label='w/ Hazardous')\n",
    "plt.legend(fontsize=10)\n",
    "plt.xticks(fontsize=20)\n",
    "plt.xlabel('%support', fontsize=15)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bbc58e2a-bafb-437c-b5f7-b2cb09dfb020",
   "metadata": {},
   "outputs": [],
   "source": [
    "help(apriori)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "a0414728-824c-46c8-84f6-a29115548332",
   "metadata": {},
   "outputs": [],
   "source": [
    "results = []\n",
    "for support in range(1, 21):\n",
    "    for confidence in range(1, 61):\n",
    "        itemsets = apriori(X, supp=support, zmin=3, target='r', conf=confidence, report='SCl')\n",
    "        for e in itemsets: \n",
    "            results.append({\n",
    "                'supp': e[2],\n",
    "                'conf': e[3],\n",
    "                'lift': e[4]\n",
    "            })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "b565da0f-25c8-46d5-9de4-344374a33bc4",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_ = pd.DataFrame(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "6c07620d-912a-4c00-bd73-4efc34b90ba8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_lift5 = df_[df_['lift'] <= 5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "fb1fbedb-ae19-465f-ba0c-37d238f11fc7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_lift5 = df_lift5.sample(100000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "d0c833de-8607-4181-b058-23895438faaf",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.show()\n",
    "plt.scatter(df_['conf'], df_['supp'], c=df_['lift'], cmap='viridis')\n",
    "plt.xlabel(\"confidence\")\n",
    "plt.ylabel(\"support\")\n",
    "plt.colorbar(label=\"lift\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "5cab1731-1265-4ff4-a1fd-c4fab83f20b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>seismoacoustic</th>\n",
       "      <th>shift</th>\n",
       "      <th>nbumps4</th>\n",
       "      <th>nbumps5</th>\n",
       "      <th>energy</th>\n",
       "      <th>class</th>\n",
       "      <th>GenergyBin</th>\n",
       "      <th>GpulsBin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>2000_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(99.999, 11560.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>3000_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2558</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(52010.0, 1766860.0]_Genergy</td>\n",
       "      <td>(661.5, 3915.0]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2559</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2560</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2561</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2562</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2563 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      seismoacoustic               shift    nbumps4    nbumps5       energy  \\\n",
       "0     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "1     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  2000_Energy   \n",
       "2     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "3     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  3000_Energy   \n",
       "4     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "...              ...                 ...        ...        ...          ...   \n",
       "2558  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2559  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2560  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2561  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2562  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "\n",
       "              class                    GenergyBin               GpulsBin  \n",
       "0     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "1     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "2     Non_Hazardous     (99.999, 11560.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "3     Non_Hazardous    (25390.0, 52010.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "4     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls  \n",
       "...             ...                           ...                    ...  \n",
       "2558  Non_Hazardous  (52010.0, 1766860.0]_Genergy  (661.5, 3915.0]_Gpuls  \n",
       "2559  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls  \n",
       "2560  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls  \n",
       "2561  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls  \n",
       "2562  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls  \n",
       "\n",
       "[2563 rows x 8 columns]"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "77465e85-2ee6-495e-9b41-03943b127ba8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Prediction'] = \"NotPredicted\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "5b52073e-c038-4dd0-b436-915dd0ab5641",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>seismoacoustic</th>\n",
       "      <th>shift</th>\n",
       "      <th>nbumps4</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(99.999, 11560.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>3000_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2558</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(52010.0, 1766860.0]_Genergy</td>\n",
       "      <td>(661.5, 3915.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2559</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2560</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2561</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
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       "    <tr>\n",
       "      <th>2562</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2563 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      seismoacoustic               shift    nbumps4    nbumps5       energy  \\\n",
       "0     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "1     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  2000_Energy   \n",
       "2     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "3     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  3000_Energy   \n",
       "4     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "...              ...                 ...        ...        ...          ...   \n",
       "2558  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2559  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2560  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2561  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2562  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "\n",
       "              class                    GenergyBin               GpulsBin  \\\n",
       "0     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "1     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "2     Non_Hazardous     (99.999, 11560.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "3     Non_Hazardous    (25390.0, 52010.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "4     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "...             ...                           ...                    ...   \n",
       "2558  Non_Hazardous  (52010.0, 1766860.0]_Genergy  (661.5, 3915.0]_Gpuls   \n",
       "2559  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2560  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2561  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "2562  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "\n",
       "        Prediction  \n",
       "0     NotPredicted  \n",
       "1     NotPredicted  \n",
       "2     NotPredicted  \n",
       "3     NotPredicted  \n",
       "4     NotPredicted  \n",
       "...            ...  \n",
       "2558  NotPredicted  \n",
       "2559  NotPredicted  \n",
       "2560  NotPredicted  \n",
       "2561  NotPredicted  \n",
       "2562  NotPredicted  \n",
       "\n",
       "[2563 rows x 9 columns]"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "18b2b520-ce54-4660-b4a8-57686c6719cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Prediction']  = np.where(np.logical_and(df['shift'] == 'Coal_getting_shift', (np.logical_and(df['GenergyBin'] == '(52010.0, 1766860.0]_Genergy' ,df['GpulsBin'] == '(661.5, 3915.0]_Gpuls'))),str('Hazardous'),df['Prediction'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "f76e955a-d610-408a-9d97-a7d06fb8a665",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>seismoacoustic</th>\n",
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       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
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       "      <th>1</th>\n",
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       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
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       "      <td>Non_Hazardous</td>\n",
       "      <td>(99.999, 11560.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>3000_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2558</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(52010.0, 1766860.0]_Genergy</td>\n",
       "      <td>(661.5, 3915.0]_Gpuls</td>\n",
       "      <td>Hazardous</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2559</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2560</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2561</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2562</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2563 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      seismoacoustic               shift    nbumps4    nbumps5       energy  \\\n",
       "0     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "1     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  2000_Energy   \n",
       "2     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "3     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  3000_Energy   \n",
       "4     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "...              ...                 ...        ...        ...          ...   \n",
       "2558  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2559  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2560  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2561  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2562  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "\n",
       "              class                    GenergyBin               GpulsBin  \\\n",
       "0     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "1     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "2     Non_Hazardous     (99.999, 11560.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "3     Non_Hazardous    (25390.0, 52010.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "4     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "...             ...                           ...                    ...   \n",
       "2558  Non_Hazardous  (52010.0, 1766860.0]_Genergy  (661.5, 3915.0]_Gpuls   \n",
       "2559  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2560  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2561  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "2562  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "\n",
       "        Prediction  \n",
       "0     NotPredicted  \n",
       "1     NotPredicted  \n",
       "2     NotPredicted  \n",
       "3     NotPredicted  \n",
       "4     NotPredicted  \n",
       "...            ...  \n",
       "2558     Hazardous  \n",
       "2559  NotPredicted  \n",
       "2560  NotPredicted  \n",
       "2561  NotPredicted  \n",
       "2562  NotPredicted  \n",
       "\n",
       "[2563 rows x 9 columns]"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "f235f0ab-8b23-454b-898d-73704c0faebe",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Prediction']  = np.where(np.logical_and(df['nbumps4'] == '0_Nbumps4', (np.logical_and(df['GenergyBin'] == '(52010.0, 1766860.0]_Genergy' ,df['GpulsBin'] == '(661.5, 3915.0]_Gpuls'))),str('Hazardous'),df['Prediction'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "4abffeeb-97fc-491e-a622-4e976353d563",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>seismoacoustic</th>\n",
       "      <th>shift</th>\n",
       "      <th>nbumps4</th>\n",
       "      <th>nbumps5</th>\n",
       "      <th>energy</th>\n",
       "      <th>class</th>\n",
       "      <th>GenergyBin</th>\n",
       "      <th>GpulsBin</th>\n",
       "      <th>Prediction</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Lack_of_hazard</td>\n",
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       "      <td>0_Nbumps5</td>\n",
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       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
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       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(99.999, 11560.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>3000_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2558</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(52010.0, 1766860.0]_Genergy</td>\n",
       "      <td>(661.5, 3915.0]_Gpuls</td>\n",
       "      <td>Hazardous</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2559</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2560</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2561</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2562</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2563 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      seismoacoustic               shift    nbumps4    nbumps5       energy  \\\n",
       "0     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "1     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  2000_Energy   \n",
       "2     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "3     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  3000_Energy   \n",
       "4     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "...              ...                 ...        ...        ...          ...   \n",
       "2558  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2559  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2560  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2561  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2562  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "\n",
       "              class                    GenergyBin               GpulsBin  \\\n",
       "0     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "1     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "2     Non_Hazardous     (99.999, 11560.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "3     Non_Hazardous    (25390.0, 52010.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "4     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "...             ...                           ...                    ...   \n",
       "2558  Non_Hazardous  (52010.0, 1766860.0]_Genergy  (661.5, 3915.0]_Gpuls   \n",
       "2559  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2560  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2561  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "2562  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "\n",
       "        Prediction  \n",
       "0     NotPredicted  \n",
       "1     NotPredicted  \n",
       "2     NotPredicted  \n",
       "3     NotPredicted  \n",
       "4     NotPredicted  \n",
       "...            ...  \n",
       "2558     Hazardous  \n",
       "2559  NotPredicted  \n",
       "2560  NotPredicted  \n",
       "2561  NotPredicted  \n",
       "2562  NotPredicted  \n",
       "\n",
       "[2563 rows x 9 columns]"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "12baa774-7381-4103-9380-d3ce0c6e5c74",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Prediction']  = np.where(np.logical_and(df['seismoacoustic'] == 'Lack_of_hazard', (np.logical_and(df['GenergyBin'] == '(52010.0, 1766860.0]_Genergy' ,df['GpulsBin'] == '(661.5, 3915.0]_Gpuls'))),str('Hazardous'),df['Prediction'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "b35aa128-0c42-4583-bffd-e3c64d0981c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>(1.999, 189.0]_Gpuls</td>\n",
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       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
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       "      <td>0_Nbumps5</td>\n",
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       "      <td>(99.999, 11560.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>3000_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2558</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(52010.0, 1766860.0]_Genergy</td>\n",
       "      <td>(661.5, 3915.0]_Gpuls</td>\n",
       "      <td>Hazardous</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2559</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2560</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2561</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2562</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2563 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      seismoacoustic               shift    nbumps4    nbumps5       energy  \\\n",
       "0     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "1     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  2000_Energy   \n",
       "2     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "3     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  3000_Energy   \n",
       "4     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "...              ...                 ...        ...        ...          ...   \n",
       "2558  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2559  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2560  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2561  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2562  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "\n",
       "              class                    GenergyBin               GpulsBin  \\\n",
       "0     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "1     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "2     Non_Hazardous     (99.999, 11560.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "3     Non_Hazardous    (25390.0, 52010.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "4     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "...             ...                           ...                    ...   \n",
       "2558  Non_Hazardous  (52010.0, 1766860.0]_Genergy  (661.5, 3915.0]_Gpuls   \n",
       "2559  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2560  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2561  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "2562  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "\n",
       "        Prediction  \n",
       "0     NotPredicted  \n",
       "1     NotPredicted  \n",
       "2     NotPredicted  \n",
       "3     NotPredicted  \n",
       "4     NotPredicted  \n",
       "...            ...  \n",
       "2558     Hazardous  \n",
       "2559  NotPredicted  \n",
       "2560  NotPredicted  \n",
       "2561  NotPredicted  \n",
       "2562  NotPredicted  \n",
       "\n",
       "[2563 rows x 9 columns]"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "e0401a40-274f-45cd-912b-15362ab52b39",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Prediction']  = np.where(np.logical_and(df['shift'] == 'Coal_getting_shift', (np.logical_and(df['nbumps4'] == '0_Nbumps4', (np.logical_and(df['GenergyBin'] == '(52010.0, 1766860.0]_Genergy' ,df['GpulsBin'] == '(661.5, 3915.0]_Gpuls'))))),str('Hazardous'),df['Prediction'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "b3aafec8-52c0-4e3a-8087-6571863ab021",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>seismoacoustic</th>\n",
       "      <th>shift</th>\n",
       "      <th>nbumps4</th>\n",
       "      <th>nbumps5</th>\n",
       "      <th>energy</th>\n",
       "      <th>class</th>\n",
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       "      <th>0</th>\n",
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       "      <td>(1.999, 189.0]_Gpuls</td>\n",
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       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
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       "      <td>(99.999, 11560.0]_Genergy</td>\n",
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       "      <td>NotPredicted</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>3000_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
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       "      <th>4</th>\n",
       "      <td>Lack_of_hazard</td>\n",
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       "      <td>0_Nbumps5</td>\n",
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       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2558</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(52010.0, 1766860.0]_Genergy</td>\n",
       "      <td>(661.5, 3915.0]_Gpuls</td>\n",
       "      <td>Hazardous</td>\n",
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       "    <tr>\n",
       "      <th>2559</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
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       "    <tr>\n",
       "      <th>2560</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2561</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2562</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
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       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2563 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      seismoacoustic               shift    nbumps4    nbumps5       energy  \\\n",
       "0     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "1     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  2000_Energy   \n",
       "2     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "3     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  3000_Energy   \n",
       "4     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "...              ...                 ...        ...        ...          ...   \n",
       "2558  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2559  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2560  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2561  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2562  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "\n",
       "              class                    GenergyBin               GpulsBin  \\\n",
       "0     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "1     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "2     Non_Hazardous     (99.999, 11560.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "3     Non_Hazardous    (25390.0, 52010.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "4     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "...             ...                           ...                    ...   \n",
       "2558  Non_Hazardous  (52010.0, 1766860.0]_Genergy  (661.5, 3915.0]_Gpuls   \n",
       "2559  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2560  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2561  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "2562  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "\n",
       "        Prediction  \n",
       "0     NotPredicted  \n",
       "1     NotPredicted  \n",
       "2     NotPredicted  \n",
       "3     NotPredicted  \n",
       "4     NotPredicted  \n",
       "...            ...  \n",
       "2558     Hazardous  \n",
       "2559  NotPredicted  \n",
       "2560  NotPredicted  \n",
       "2561  NotPredicted  \n",
       "2562  NotPredicted  \n",
       "\n",
       "[2563 rows x 9 columns]"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "409857b0-5d82-4d3d-9cfe-3edfff220461",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Prediction']  = np.where(np.logical_and(df['nbumps5'] == '0_Nbumps5', (np.logical_and(df['shift'] == 'Coal_getting_shift', (np.logical_and(df['nbumps4'] == '0_Nbumps4', (np.logical_and(df['GenergyBin'] == '(52010.0, 1766860.0]_Genergy' ,df['GpulsBin'] == '(661.5, 3915.0]_Gpuls'))))))),str('Hazardous'),df['Prediction'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "70331a1e-7075-40f1-b29b-908091d3f3d7",
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
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       "      <td>0_Nbumps5</td>\n",
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       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
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       "      <th>4</th>\n",
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       "      <td>0_Nbumps5</td>\n",
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       "      <td>(1.999, 189.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2558</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(52010.0, 1766860.0]_Genergy</td>\n",
       "      <td>(661.5, 3915.0]_Gpuls</td>\n",
       "      <td>Hazardous</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2559</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
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       "    <tr>\n",
       "      <th>2560</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2561</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2562</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>NotPredicted</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2563 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      seismoacoustic               shift    nbumps4    nbumps5       energy  \\\n",
       "0     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "1     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  2000_Energy   \n",
       "2     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "3     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  3000_Energy   \n",
       "4     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "...              ...                 ...        ...        ...          ...   \n",
       "2558  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2559  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2560  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2561  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2562  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "\n",
       "              class                    GenergyBin               GpulsBin  \\\n",
       "0     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "1     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "2     Non_Hazardous     (99.999, 11560.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "3     Non_Hazardous    (25390.0, 52010.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "4     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "...             ...                           ...                    ...   \n",
       "2558  Non_Hazardous  (52010.0, 1766860.0]_Genergy  (661.5, 3915.0]_Gpuls   \n",
       "2559  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2560  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2561  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "2562  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "\n",
       "        Prediction  \n",
       "0     NotPredicted  \n",
       "1     NotPredicted  \n",
       "2     NotPredicted  \n",
       "3     NotPredicted  \n",
       "4     NotPredicted  \n",
       "...            ...  \n",
       "2558     Hazardous  \n",
       "2559  NotPredicted  \n",
       "2560  NotPredicted  \n",
       "2561  NotPredicted  \n",
       "2562  NotPredicted  \n",
       "\n",
       "[2563 rows x 9 columns]"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "e0820295-316a-4683-ba9a-5abb23425e83",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Prediction']  = np.where(np.logical_and(df['nbumps5'] == '0_Nbumps5', (np.logical_and(df['seismoacoustic'] == 'Lack_of_hazard', (np.logical_and(df['GenergyBin'] == '(52010.0, 1766860.0]_Genergy' ,df['GpulsBin'] == '(661.5, 3915.0]_Gpuls'))))),str('Hazardous'),df['Prediction'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "94b43b89-42de-4766-a221-d43f4fc8e990",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>seismoacoustic</th>\n",
       "      <th>shift</th>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lack_of_hazard</td>\n",
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       "      <td>0_Nbumps4</td>\n",
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       "      <td>Non_Hazardous</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Preparation_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>3000_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2558</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
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       "      <td>Lack_of_hazard</td>\n",
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       "      <td>0_Nbumps5</td>\n",
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       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
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       "      <td>Non_Hazardous</td>\n",
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       "      <td>Lack_of_hazard</td>\n",
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       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>Non_Hazardous</td>\n",
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       "    <tr>\n",
       "      <th>2561</th>\n",
       "      <td>Lack_of_hazard</td>\n",
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       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
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       "      <td>Lack_of_hazard</td>\n",
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       "      <td>0_Nbumps5</td>\n",
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       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2563 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      seismoacoustic               shift    nbumps4    nbumps5       energy  \\\n",
       "0     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "1     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  2000_Energy   \n",
       "2     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "3     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  3000_Energy   \n",
       "4     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "...              ...                 ...        ...        ...          ...   \n",
       "2558  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2559  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2560  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2561  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2562  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "\n",
       "              class                    GenergyBin               GpulsBin  \\\n",
       "0     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "1     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "2     Non_Hazardous     (99.999, 11560.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "3     Non_Hazardous    (25390.0, 52010.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "4     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "...             ...                           ...                    ...   \n",
       "2558  Non_Hazardous  (52010.0, 1766860.0]_Genergy  (661.5, 3915.0]_Gpuls   \n",
       "2559  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2560  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2561  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "2562  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "\n",
       "         Prediction  \n",
       "0     Non_Hazardous  \n",
       "1     Non_Hazardous  \n",
       "2     Non_Hazardous  \n",
       "3     Non_Hazardous  \n",
       "4     Non_Hazardous  \n",
       "...             ...  \n",
       "2558      Hazardous  \n",
       "2559  Non_Hazardous  \n",
       "2560  Non_Hazardous  \n",
       "2561  Non_Hazardous  \n",
       "2562  Non_Hazardous  \n",
       "\n",
       "[2563 rows x 9 columns]"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "c0d17910-749f-4e01-9dc2-dce738bdf20e",
   "metadata": {},
   "outputs": [],
   "source": [
    "ppp = np.logical_and(df['nbumps4'] == '0_Nbumps4' ,df['nbumps5'] == '0_Nbumps5')\n",
    "df['Prediction']  = np.where(np.logical_and(ppp, df['Prediction'] == 'NotPredicted'),str('Non_Hazardous'),df['Prediction'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "66c6e971-f80a-4764-90ac-71a45b4d5f98",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Lack_of_hazard</td>\n",
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       "      <td>0_Nbumps5</td>\n",
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       "      <td>Lack_of_hazard</td>\n",
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       "      <td>Lack_of_hazard</td>\n",
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       "      <td>0_Nbumps5</td>\n",
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       "      <td>Non_Hazardous</td>\n",
       "      <td>(25390.0, 52010.0]_Genergy</td>\n",
       "      <td>(376.0, 661.5]_Gpuls</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2561</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2562</th>\n",
       "      <td>Lack_of_hazard</td>\n",
       "      <td>Coal_getting_shift</td>\n",
       "      <td>0_Nbumps4</td>\n",
       "      <td>0_Nbumps5</td>\n",
       "      <td>0_Energy</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "      <td>(11560.0, 25390.0]_Genergy</td>\n",
       "      <td>(189.0, 376.0]_Gpuls</td>\n",
       "      <td>Non_Hazardous</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2563 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      seismoacoustic               shift    nbumps4    nbumps5       energy  \\\n",
       "0     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "1     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  2000_Energy   \n",
       "2     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "3     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5  3000_Energy   \n",
       "4     Lack_of_hazard   Preparation_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "...              ...                 ...        ...        ...          ...   \n",
       "2558  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2559  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2560  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2561  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "2562  Lack_of_hazard  Coal_getting_shift  0_Nbumps4  0_Nbumps5     0_Energy   \n",
       "\n",
       "              class                    GenergyBin               GpulsBin  \\\n",
       "0     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "1     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "2     Non_Hazardous     (99.999, 11560.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "3     Non_Hazardous    (25390.0, 52010.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "4     Non_Hazardous    (11560.0, 25390.0]_Genergy   (1.999, 189.0]_Gpuls   \n",
       "...             ...                           ...                    ...   \n",
       "2558  Non_Hazardous  (52010.0, 1766860.0]_Genergy  (661.5, 3915.0]_Gpuls   \n",
       "2559  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2560  Non_Hazardous    (25390.0, 52010.0]_Genergy   (376.0, 661.5]_Gpuls   \n",
       "2561  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "2562  Non_Hazardous    (11560.0, 25390.0]_Genergy   (189.0, 376.0]_Gpuls   \n",
       "\n",
       "         Prediction  \n",
       "0     Non_Hazardous  \n",
       "1     Non_Hazardous  \n",
       "2     Non_Hazardous  \n",
       "3     Non_Hazardous  \n",
       "4     Non_Hazardous  \n",
       "...             ...  \n",
       "2558      Hazardous  \n",
       "2559  Non_Hazardous  \n",
       "2560  Non_Hazardous  \n",
       "2561  Non_Hazardous  \n",
       "2562  Non_Hazardous  \n",
       "\n",
       "[2563 rows x 9 columns]"
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "851db2a4-9a24-4372-9627-f80b164d9d79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "68"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df[df['Prediction'] == 'NotPredicted'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "8f43ac3b-5bed-445e-8775-aa8fac13961e",
   "metadata": {},
   "outputs": [],
   "source": [
    "pp = np.logical_and(df['shift'] == 'Coal_getting_shift' ,df['nbumps5'] == '0_Nbumps5')\n",
    "df['Prediction']  = np.where(np.logical_and(pp, df['Prediction'] == 'NotPredicted'),str('Non_Hazardous'),df['Prediction'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "4f4dfc8e-0bdf-482d-8423-f975b5da316b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df[df['Prediction'] == 'NotPredicted'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "560f9aee-1240-489b-b66f-2285910776b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "p = np.logical_and(df['seismoacoustic'] == 'Lack_of_hazard' ,df['nbumps5'] == '0_Nbumps5')\n",
    "df['Prediction']  = np.where(np.logical_and(p, df['Prediction'] == 'NotPredicted'),str('Non_Hazardous'),df['Prediction'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "8139c010-bbb4-407c-abe8-43bedcc795ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df[df['Prediction'] == 'NotPredicted'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "eb763ed4-bb1c-4378-9bbf-5bd7a95065ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "pppp = np.logical_and(df['shift'] == 'Coal_getting_shift' ,df['nbumps4'] == '0_Nbumps4')\n",
    "df['Prediction']  = np.where(np.logical_and(pppp, df['Prediction'] == 'NotPredicted'),str('Non_Hazardous'),df['Prediction'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "id": "50693450-11c1-4278-8d68-22ad48588809",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df[df['Prediction'] == 'NotPredicted'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "628d4daf-053b-4806-a2a2-570751466b83",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Prediction']  = np.where(df['Prediction'] == 'NotPredicted',str('Non_Hazardous'),df['Prediction'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "8a79bb69-2197-4701-baa7-a82767342f01",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df[df['Prediction'] == 'NotPredicted'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "26432e44-87ab-49d9-b97e-3e9c64795572",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2112"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df[df['Prediction'] == df['class']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "94f9079f-311a-4fc8-a7c0-1626e60bcf46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "451"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df[df.Prediction != df['class']]) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "bf87e1f7-22c1-46d5-bde0-2adbe25a02ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "93"
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Falsi negativi\n",
    "len(df[(df[\"class\"] == 'Hazardous') & (df['Prediction'] == 'Non_Hazardous')])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "id": "2294fbc8-2f76-4067-962a-d68a4fa19d4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "358"
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Falsi positivi\n",
    "len(df[(df[\"class\"] == 'Non_Hazardous') & (df['Prediction'] == 'Hazardous')])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "id": "7b1d6cda-de11-4063-a3bb-bfc1c2a772ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "77"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Veri positivi\n",
    "len(df[(df[\"class\"] == 'Hazardous') & (df['Prediction'] == 'Hazardous')])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "id": "917f52c1-f964-4f8e-8057-80d9a3913eda",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2035"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Veri negativi\n",
    "len(df[(df[\"class\"] == 'Non_Hazardous') & (df['Prediction'] == 'Non_Hazardous')])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "id": "fd1d56df-2a5e-4953-af6b-76085011e03b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import precision_recall_fscore_support"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "id": "80ef017a-01b8-4f26-bc49-0b7e14a4c4bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0.5666542433670383, 0.6516690838474963, 0.5773943817739438, None)\n"
     ]
    }
   ],
   "source": [
    "y_true = df['class']\n",
    "y_pred = df['Prediction']\n",
    "precision_recall_fscore_support(y_true, y_pred, average='macro')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "id": "67385d58-0cf7-4a1f-8c6a-0b8d5002dc60",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import accuracy_score, classification_report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "id": "182f0b66-0ae0-4c86-9ebc-5ccfdee9d791",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8240343347639485"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_true, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "id": "55f0cb0a-b257-42f3-8318-d07ab56452ee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               precision    recall  f1-score   support\n",
      "\n",
      "    Hazardous       0.18      0.45      0.25       170\n",
      "Non_Hazardous       0.96      0.85      0.90      2393\n",
      "\n",
      "     accuracy                           0.82      2563\n",
      "    macro avg       0.57      0.65      0.58      2563\n",
      " weighted avg       0.90      0.82      0.86      2563\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_true, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "54b8e1fb-5950-48df-a707-ecadbc160679",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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