practica_3_IA_B.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "41eab4c8-0882-435f-a652-0adb7d645e48",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Para mas información, consulta el GitHub [https://github.com/Zygmut/Practica_3_IA]\n",
    "# Autores: Palmer Pérez, Rubén; Torres Torres, Marc; Orr, Kieran Donal"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a60c2ad8",
   "metadata": {},
   "source": [
    "# Setup\n",
    "Importamos todos los paquetes necesarios para la práctica. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "fc2ffd68-c543-49bd-9413-e0e84c0ffa93",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import preprocessing\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.linear_model import LogisticRegression, Perceptron\n",
    "from sklearn.ensemble import RandomForestClassifier "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7d6bb1b",
   "metadata": {},
   "source": [
    "Creamos un conjunto de variables para facil acceso y cambio de parámetros"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "99381966",
   "metadata": {},
   "outputs": [],
   "source": [
    "TEST_SIZE = 0.33             # Proportion for test size in relation to the dataset\n",
    "CORRELATION_THRESHOLD = 0.05 # Threshold to remove columns in the correlation matrix\n",
    "ALTERNATIVE_MODE = False     # Quality (0-10) or (\"bad\", \"average\", \"good\")\n",
    "QUALITY_THRESHOLD = 6        # Threshold that defines a range for each quality of wine (\"bad\", \"average\", \"good\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8625d1cb",
   "metadata": {},
   "source": [
    "Definimos una variable `DEBUG` (y su método de uso) que, en caso de estar activada, nos dará información adicional a lo largo de la ejecución del proyecto "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "d6fbe7e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "DEBUG = True \n",
    "\n",
    "def debugPrint(string):\n",
    "    if DEBUG : print(f\"[🐛] {string}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30db9b88",
   "metadata": {},
   "source": [
    "# El dataset\n",
    "Cargamos los datasets y les añadimos la columna `type` que nos permitara reconocer de que tipo son una vez juntados los datasets. Si `type = 0` el vino será blanco, de lo contrario sera rojo."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "5ca37e25-3df9-436a-85d4-435b969ae0c6",
   "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>type</th>\n",
       "      <th>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.36</td>\n",
       "      <td>20.7</td>\n",
       "      <td>0.045</td>\n",
       "      <td>45.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>1.0010</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0.45</td>\n",
       "      <td>8.8</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.34</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.049</td>\n",
       "      <td>14.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>0.9940</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.49</td>\n",
       "      <td>9.5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>8.1</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.40</td>\n",
       "      <td>6.9</td>\n",
       "      <td>0.050</td>\n",
       "      <td>30.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>0.9951</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.44</td>\n",
       "      <td>10.1</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.32</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.058</td>\n",
       "      <td>47.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>0.9956</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.40</td>\n",
       "      <td>9.9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.32</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.058</td>\n",
       "      <td>47.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>0.9956</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.40</td>\n",
       "      <td>9.9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   type  fixed acidity  volatile acidity  citric acid  residual sugar  \\\n",
       "0     0            7.0              0.27         0.36            20.7   \n",
       "1     0            6.3              0.30         0.34             1.6   \n",
       "2     0            8.1              0.28         0.40             6.9   \n",
       "3     0            7.2              0.23         0.32             8.5   \n",
       "4     0            7.2              0.23         0.32             8.5   \n",
       "\n",
       "   chlorides  free sulfur dioxide  total sulfur dioxide  density    pH  \\\n",
       "0      0.045                 45.0                 170.0   1.0010  3.00   \n",
       "1      0.049                 14.0                 132.0   0.9940  3.30   \n",
       "2      0.050                 30.0                  97.0   0.9951  3.26   \n",
       "3      0.058                 47.0                 186.0   0.9956  3.19   \n",
       "4      0.058                 47.0                 186.0   0.9956  3.19   \n",
       "\n",
       "   sulphates  alcohol  quality  \n",
       "0       0.45      8.8        6  \n",
       "1       0.49      9.5        6  \n",
       "2       0.44     10.1        6  \n",
       "3       0.40      9.9        6  \n",
       "4       0.40      9.9        6  "
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "white = pd.read_csv(\"dataset/winequality-white.csv\", sep=';')\n",
    "white.insert(0, 'type', 0)\n",
    "red = pd.read_csv(\"dataset/winequality-red.csv\", sep= ';')\n",
    "red.insert(0, 'type', 1)\n",
    "df = pd.concat([white, red])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26086f36",
   "metadata": {},
   "source": [
    "Preparamos los datos del dataset eliminando todos los posibles valores nulos y transformando los valores que no sean `np.float64` o `np.int64` "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "6f5728a5-6567-4f55-8219-eade476c8e37",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Preparacion del dataset\n",
    "\n",
    "labelencoder = LabelEncoder()\n",
    "\n",
    "if not df[df.isna().any(axis=1)].shape[0] == 0 :\n",
    "    debugPrint(\"Valores nulos eliminados para el dataframe\")\n",
    "    \n",
    "df.dropna(inplace=True) # Eliminacion de valores nullos\n",
    "\n",
    "for column in df.columns: # Transformar posibles valores no numericos\n",
    "    if not df[column].dtype in (np.float64, np.int64):\n",
    "        df[column] = labelencoder.fit_transform(df[column])\n",
    "        debugPrint(f\"Los valores de {column} se han transformado a numericos\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a797e1c",
   "metadata": {},
   "source": [
    "## Visualización de datos\n",
    "En este apartado visualizaremos los datos para un entendimiento gráfico de nuestras carácteres.\n",
    "\n",
    "Primero visualizaremos la disposición de nuestros datos con respecto a la **calidad**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "a547235f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='quality', ylabel='count'>"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "sns.set(style=\"white\")\n",
    "sns.countplot(x=df[\"quality\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fdd32ac0",
   "metadata": {},
   "source": [
    "Como podemos ver aqui los datos estan distribuidos como una distribución normal, hay muchos datos por el centro en los valores de 5, 6 y 7 y pocos datos en los extremos. Eso es de esperar con una muestra de tamaño tan grande pero, el hecho de que haya tan pocos datos en los extremos nos va a causar problemas luego a la hora de hacer las predicciones sino categorizamos.  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e4df508",
   "metadata": {},
   "source": [
    "Otra representación que puede ser interesante sería poder ver la diferencia de calidad entre los vinos tintos y los vinos blancos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "259fb9ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='quality', ylabel='count'>"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "sns.set(style=\"white\")\n",
    "sns.countplot(x=white[\"quality\"])\n",
    "\n",
    "plt.figure(figsize=(10,10))\n",
    "sns.set(style=\"white\")\n",
    "sns.countplot(x=red[\"quality\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39d47489",
   "metadata": {},
   "source": [
    "Podemos observar que, ademas de tener muchas mas muestras en el vino blanco, el vino tinto suele tener notas más bajas. Podemos calcular una media rápidamente para poder reasegurarlo."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "b70e6b87",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Media de los vinos blancos: 5.87790935075541\t Media de los vinos tintos: 5.6360225140712945\n"
     ]
    }
   ],
   "source": [
    "print(\"Media de los vinos blancos: {}\\t Media de los vinos tintos: {}\".format(np.mean(white[\"quality\"]), np.mean(red[\"quality\"])))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8dcad37",
   "metadata": {},
   "source": [
    "Podemos tambien prinetar todos los posibles valores de las caracteristicas para tener una idea grafica de como es nuestro dataset completo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "64eca068",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:ylabel='Density'>, <AxesSubplot:ylabel='Density'>,\n",
       "        <AxesSubplot:ylabel='Density'>],\n",
       "       [<AxesSubplot:ylabel='Density'>, <AxesSubplot:ylabel='Density'>,\n",
       "        <AxesSubplot:ylabel='Density'>],\n",
       "       [<AxesSubplot:ylabel='Density'>, <AxesSubplot:ylabel='Density'>,\n",
       "        <AxesSubplot:ylabel='Density'>],\n",
       "       [<AxesSubplot:ylabel='Density'>, <AxesSubplot:ylabel='Density'>,\n",
       "        <AxesSubplot:ylabel='Density'>]], dtype=object)"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1296x864 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1296x864 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Histogramas\n",
    "df_show = df.drop(\"type\", axis = 1)\n",
    "df_show.hist(figsize=(18,12))\n",
    "\n",
    "# Densidad de datos \n",
    "df_show.plot(kind='density', subplots = True, layout=(4,3), sharex=False, figsize=(18,12))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44e716ce",
   "metadata": {},
   "source": [
    "## Matriz de correlación\n",
    "Como ya hemos visto en la visualización de los datos tenemos caracteristicas que, respecto a calidad, no nos ofrecen mucha variación. Para asegurarnos de esta independecia entre caracteristicas, analizaremos la matriz de correlación. Tenemos una variable llamada `CORRELATION_THRESHOLD` que define la desviación mínima que aceptamos. Es decir, si tenemos una correlación de `0.03` con respecto a _quality_, podemos decir que son suficientemente independientes como para no tenerlas en cuenta. De esta manera, podemos reducir el tamaños de las caracteristicas para el entrenamiento de nuestro modelos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "f7bec265",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[🐛] Removed column 4\n",
      "[🐛] Removed column 7\n",
      "[🐛] Removed column 9\n",
      "[🐛] Removed column 10\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,10))\n",
    "\n",
    "removed_columns = []\n",
    "\n",
    "for i in range(len(df.corr()[\"quality\"])):\n",
    "    if abs(df.corr()[\"quality\"][i]) < CORRELATION_THRESHOLD:\n",
    "        debugPrint(f\"Removed column {i}\") \n",
    "        removed_columns.append(i)\n",
    "        \n",
    "\n",
    "df.drop(df.columns[removed_columns], axis=1, inplace = True)\n",
    "  \n",
    "sns.heatmap(df.corr(), annot=True, square=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95b43145",
   "metadata": {},
   "source": [
    "Adicionalmente, definiremos unos rangos de calidad de tal manera que :\n",
    "- baja &rarr; \"quality\" < `QUALITY_THRESHOLD` \n",
    "- media &rarr; \"quality\" = `QUALITY_THRESHOLD` \n",
    "- alta &rarr; \"quality\" > `QUALITY_THRESHOLD` \n",
    "\n",
    "Lo tomaremos tal que:\n",
    "- baja &rarr; 1 \n",
    "- media &rarr; 2\n",
    "- alta &rarr; 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "89a13c0a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[🐛] [6 5 7 8 4 3 9]\n"
     ]
    }
   ],
   "source": [
    "if ALTERNATIVE_MODE :\n",
    "    debugPrint(\"Alternative mode detected\")\n",
    "    df[\"quality\"] = df[\"quality\"].apply(lambda y: 1 if y<QUALITY_THRESHOLD else y)\n",
    "    df[\"quality\"] = df[\"quality\"].apply(lambda y: 2 if y==QUALITY_THRESHOLD else y)\n",
    "    df[\"quality\"] = df[\"quality\"].apply(lambda y: 3 if y>QUALITY_THRESHOLD else y)\n",
    "\n",
    "debugPrint(df[\"quality\"].unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54484e21",
   "metadata": {},
   "source": [
    "Poder juntar las puntuaciones en categorias nos ayudara mucho a la hora de hacer predicciones ya que puntuaciones como el 9 tiene solo 5 ejemplos, hacer predicciones con una muestra tan pequeña resulta ser difícil. Pero si los juntamos con lo 8 y 7 nos da mas data para hacer tests."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ec45bf8",
   "metadata": {},
   "source": [
    "## Escalado de datos\n",
    "Por último, escalamos los datos y separamos las \"features\" y etiquetas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "7e0b4750",
   "metadata": {},
   "outputs": [],
   "source": [
    "m_M_scaler = preprocessing.MinMaxScaler()\n",
    "\n",
    "# Separamos las features de las etiquetas \n",
    "y = df[\"quality\"]\n",
    "x = df.drop(\"quality\", axis=1)\n",
    "\n",
    "# Escalamos los datos\n",
    "x = m_M_scaler.fit_transform(x)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b9936b3",
   "metadata": {},
   "source": [
    "### Separación del conjunto de entrenamiento, validación y testeo\n",
    "Una vez obtenido nuestro dataset con sus valores procesados, creamos los 2 subconjuntos de datos que nos permitirán entrenar nuestros modelos (entrenamiento y testeo). El subconjutno de validación se creará posteriormente."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "000c84a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train, x_test, y_train, y_test = train_test_split(x,y,test_size=TEST_SIZE, stratify=y , random_state=42)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85a40bcd",
   "metadata": {},
   "source": [
    "# Modelos\n",
    "Una vez preparado nuestros datasets de entrenamiento y testeo, podemos usarlos para nuestros modelos de machine learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "8dcf0ee0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Definimos las etiquetas\n",
    "targetType = [\"bad\", \"average\", \"good\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb921537",
   "metadata": {},
   "source": [
    "## Aplicación"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf84350b",
   "metadata": {},
   "source": [
    "Podemos observar que para la solución cuya salida es una nota tenemos varias `zero_division`. Esto ocurre debido a una desproporción de datos. Esto se podría solucionar si tuviesemos más datos para todas las posibles calidades de nuestro dataset. Para esta solución, en vez de generar datos a partir de los actuales mediante algún tipo de interpolación, trataremos estas `zero_division` como 1 "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42f4d45f",
   "metadata": {},
   "source": [
    "### Regresión logística\n",
    "Debemos aumentar las `max_iter` ya que el número de iteraciónes base (100) no es suficiente"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "c80f090c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           3       1.00      0.00      0.00        10\n",
      "           4       1.00      0.00      0.00        71\n",
      "           5       0.57      0.61      0.59       706\n",
      "           6       0.51      0.69      0.59       936\n",
      "           7       0.42      0.14      0.21       356\n",
      "           8       1.00      0.00      0.00        64\n",
      "           9       1.00      0.00      0.00         2\n",
      "\n",
      "    accuracy                           0.53      2145\n",
      "   macro avg       0.79      0.21      0.20      2145\n",
      "weighted avg       0.55      0.53      0.49      2145\n",
      "\n"
     ]
    }
   ],
   "source": [
    "clr = LogisticRegression(random_state=0, max_iter=200).fit(x_train, y_train) # Aumentamos las iteraciónes \n",
    "y_hat = clr.predict(x_test)\n",
    "\n",
    "if ALTERNATIVE_MODE:\n",
    "    print(classification_report(y_test, y_hat, target_names=targetType))\n",
    "else: \n",
    "    print(classification_report(y_test, y_hat, zero_division=1)) # Evitamos el error de \"división por zero\" "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ae444af",
   "metadata": {},
   "source": [
    "### Perceptron"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "b2226096",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           3       1.00      0.00      0.00        10\n",
      "           4       0.29      0.10      0.15        71\n",
      "           5       0.58      0.28      0.38       706\n",
      "           6       0.46      0.88      0.61       936\n",
      "           7       1.00      0.00      0.00       356\n",
      "           8       1.00      0.00      0.00        64\n",
      "           9       1.00      0.00      0.00         2\n",
      "\n",
      "    accuracy                           0.48      2145\n",
      "   macro avg       0.76      0.18      0.16      2145\n",
      "weighted avg       0.61      0.48      0.40      2145\n",
      "\n"
     ]
    }
   ],
   "source": [
    "cp = Perceptron(random_state=0).fit(x_train, y_train)\n",
    "y_hat = cp.predict(x_test)\n",
    "\n",
    "if ALTERNATIVE_MODE:\n",
    "    print(classification_report(y_test, y_hat, target_names=targetType))\n",
    "else: \n",
    "    print(classification_report(y_test, y_hat, zero_division=1)) # Evitamos el error de \"división por zero\" "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f95c8613",
   "metadata": {},
   "source": [
    "### Random forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "94b5bed3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           3       1.00      0.00      0.00        10\n",
      "           4       0.29      0.10      0.15        71\n",
      "           5       0.58      0.28      0.38       706\n",
      "           6       0.46      0.88      0.61       936\n",
      "           7       1.00      0.00      0.00       356\n",
      "           8       1.00      0.00      0.00        64\n",
      "           9       1.00      0.00      0.00         2\n",
      "\n",
      "    accuracy                           0.48      2145\n",
      "   macro avg       0.76      0.18      0.16      2145\n",
      "weighted avg       0.61      0.48      0.40      2145\n",
      "\n"
     ]
    }
   ],
   "source": [
    "crf = RandomForestClassifier(random_state=0).fit(x_train, y_train)\n",
    "y_hat = cp.predict(x_test)\n",
    "\n",
    "if ALTERNATIVE_MODE:\n",
    "    print(classification_report(y_test, y_hat, target_names=targetType))\n",
    "else: \n",
    "    print(classification_report(y_test, y_hat, zero_division=1)) # Evitamos el error de \"división por zero\" "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eefe1801",
   "metadata": {},
   "source": [
    "## Analisis de los resultados"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b92747f8",
   "metadata": {},
   "source": [
    "En este apartado hemos quitado las variables con una correlacion por debajo de 0.05 al hacer eso nos van a cambiar los resultados respecto a la ultuma prueba. Igual que la ultima vez a mirar los resultados primero usando puntuaciones para hacer classes y luego lo haremos agrupandolos por bad, average and good\n",
    "\n",
    "Cuando hacemos las clases por los valores numéricos de las puntuaciones vemos que pasa lo siguiente:\n",
    " En la regressión logística seguimos con el mismo problema que cuando no quitabamos las variables con correlación menor a 0.05 las clases que no sean 5, 6 o 7 no se les predice ningun valor, los mete como falsos positivos en las de 5, 6 i 7. Eso tambien baja la precisión de esas clases. Aparte de eso tambien vemos que todos los valores de recal y precision en han bajado. Eso significa que las variables que hemos quitado ayudaban a clasificar antes.\n",
    "\n",
    " En el perceptron y el random forest vemos que siguen dando los mismos resultados los dos por lo tanto las voy a comentar juntas. Podemos ver immediatamente que ha mejorado los resultados antes solo predecia para los valores de 5 y 6 ahora tambien lo hace para 4. Aparte de eso tambien ha mejorado la precision del 5 y el recal del 6. Pero hay que mencionar que la precision de 6 ha empeorado un poco y el recal de 5 ha emperorado mucho. \n",
    "\n",
    "Cuando lo hacemos agrupandolos"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}