{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TQqrOdkY6nsy"
   },
   "source": [
    "# **Klasyfikacja za pomocą naiwnej metody bayesowskiej z rozkładem normalnym**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "SSaJsYOhz8h8"
   },
   "source": [
    "![rozklady.jpg](data:image/jpeg;base64,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)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "AlcfRFCPSXIj"
   },
   "source": [
    "# **Twierdzenie Bayesa**\n",
    "![bayes.svg](data:image/svg+xml;base64,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)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rcpTnWjOh5dq"
   },
   "source": [
    "P(A) -- oznacza prawdopodobieństwo a-priori wystąpienia klasy A (tj. prawdopodobieństwo, że dowolny przykład należy do klasy A)\n",
    "\n",
    "P(B|A) -- oznacza prawdopodobieństwo a-posteriori, że B należy do \n",
    "klasy A\n",
    "\n",
    "P(B) -- znacza prawdopodobieństwo a-priori wystąpienia przykładu B "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Yabcm4Rei2ue"
   },
   "source": [
    "![GaussianNB.png](data:image/png;base64,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)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "dsf6FnlgjiOL"
   },
   "source": [
    "# Funkcja gęstości prawdopodobieństwa rozkładu normalnego \n",
    "![gestosc.svg](data:image/svg+xml;base64,<svg xmlns:xlink="http://www.w3.org/1999/xlink" width="36.328ex" height="7.509ex" style="vertical-align: -3.171ex;" viewBox="0 -1867.7 15641.2 3233.2" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" aria-labelledby="MathJax-SVG-1-Title">
<title id="MathJax-SVG-1-Title">{\displaystyle f_{\mu ,\sigma }(x)={\frac {1}{\sigma {\sqrt {2\pi }}}}\,\exp \left({\frac {-(x-\mu )^{2}}{2\sigma ^{2}}}\right).}</title>
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   "execution_count": 1,
   "metadata": {
    "id": "v0oeHebytjNp"
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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scipy.stats as stats\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.model_selection import train_test_split\n",
    "sns.set(style=\"whitegrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "fOYTA3VVtjNw"
   },
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   "source": [
    "class NaiveBayesClassifier():\n",
    "    def calc_prior(self, features, target):\n",
    "        '''\n",
    "        Wyliczenie prawdopodobieństwa a priori\n",
    "        '''\n",
    "        self.prior = (features.groupby(target).apply(lambda x: len(x)) / self.rows).to_numpy()\n",
    "\n",
    "        return self.prior\n",
    "    \n",
    "    def calc_statistics(self, features, target):\n",
    "        '''\n",
    "        Wyliczenie średnich i wariancji dla danych\n",
    "        ''' \n",
    "        self.mean = features.groupby(target).apply(np.mean).to_numpy()\n",
    "        self.var = features.groupby(target).apply(np.var).to_numpy()\n",
    "              \n",
    "        return self.mean, self.var\n",
    "    \n",
    "    def gaussian_density(self, class_idx, x):     \n",
    "        '''\n",
    "        Wyliczenie prawdopodobieństwa z rozkładu normalnego        \n",
    "        (1/√2pi*σ) * exp((-1/2)*((x-μ)^2)/(2*σ²))\n",
    "        μ -średnia\n",
    "        σ² - wariancja\n",
    "        σ - odchylenie standardowe\n",
    "        '''\n",
    "        mean = self.mean[class_idx]\n",
    "        var = self.var[class_idx]\n",
    "        numerator = np.exp((-1/2)*((x-mean)**2) / (2 * var))\n",
    "        denominator = np.sqrt(2 * np.pi * var)\n",
    "        prob = numerator / denominator\n",
    "        return prob\n",
    "    \n",
    "    def calc_posterior(self, x):\n",
    "        '''\n",
    "        Wyliczenie prawdopodobieństwa a posteriori i zwrócenie klasy, dla której prawdopodobieństwo jest najwyższe\n",
    "        '''\n",
    "        posteriors = []\n",
    "        posteriors_no_log = []\n",
    "\n",
    "        # calculate posterior probability for each class\n",
    "        for i in range(self.count):\n",
    "            prior = np.log(self.prior[i]) # Do predykcji używane jest prawodopodobieństwo logarytmiczne\n",
    "            prior_no_log = self.prior[i] # Zwykłe prawdopodobieństwo liczymy, żeby zwrócić je z predykcjami\n",
    "\n",
    "            conditional = np.sum(np.log(self.gaussian_density(i, x))) \n",
    "            conditional_no_log = np.prod(self.gaussian_density(i, x))\n",
    "\n",
    "            posterior = prior + conditional\n",
    "            posterior_no_log = prior_no_log * conditional_no_log\n",
    "\n",
    "            posteriors.append(posterior)\n",
    "            posteriors_no_log.append(posterior_no_log)\n",
    "\n",
    "        # Zwracamy klasę o największym prawdopodobieństwie\n",
    "        return self.classes[np.argmax(posteriors)], np.max(posteriors_no_log)\n",
    "\n",
    "    def fit(self, features, target):\n",
    "        '''\n",
    "        Główna metoda trenująca model\n",
    "        '''\n",
    "        self.classes = np.unique(target)\n",
    "        self.count = len(self.classes)\n",
    "        self.feature_nums = features.shape[1]\n",
    "        self.rows = features.shape[0]\n",
    "        \n",
    "        self.calc_statistics(features, target)\n",
    "        self.calc_prior(features, target)\n",
    "        \n",
    "    def predict(self, features):\n",
    "        '''\n",
    "        Predykcja wartości dla każdego wiersza\n",
    "        '''\n",
    "        preds = [self.calc_posterior(f) for f in features.to_numpy()]\n",
    "        return preds\n",
    "\n",
    "    def accuracy(self, y_test, y_pred):\n",
    "        '''\n",
    "        Wyliczenie accuracy modelu\n",
    "        '''\n",
    "        accuracy = np.sum(y_test == y_pred) / len(y_test)\n",
    "        return accuracy\n",
    "\n",
    "    def visualize(self, y_true, y_pred, target):\n",
    "        '''\n",
    "        Narysowanie wykresu porównującego rozkład klas prawdziwych i przewidzianych\n",
    "        '''\n",
    "        tr = pd.DataFrame(data=y_true, columns=[target])\n",
    "        pr = pd.DataFrame(data=y_pred, columns=[target])\n",
    "        \n",
    "        \n",
    "        fig, ax = plt.subplots(1, 2, sharex='col', sharey='row', figsize=(15,6))\n",
    "        \n",
    "        sns.countplot(x=target, data=tr, ax=ax[0], palette='viridis', alpha=0.7, hue=target, dodge=False)\n",
    "        sns.countplot(x=target, data=pr, ax=ax[1], palette='viridis', alpha=0.7, hue=target, dodge=False)\n",
    "        \n",
    "\n",
    "        fig.suptitle('True vs Predicted Comparison', fontsize=20)\n",
    "\n",
    "        ax[0].tick_params(labelsize=12)\n",
    "        ax[1].tick_params(labelsize=12)\n",
    "        ax[0].set_title(\"Prawdziwe wartości\", fontsize=18)\n",
    "        ax[1].set_title(\"Predyckje\", fontsize=18)\n",
    "        plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 382
    },
    "id": "5-riUAGntjN2",
    "outputId": "f87f047d-bc71-41ef-a43a-17b6f7cf84c3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2948, 9) (2948,)\n",
      "(328, 9) (328,)\n"
     ]
    }
   ],
   "source": [
    "# Preprocessing danych\n",
    "\n",
    "# Uzupełnienie pustych wartości w kolumnach\n",
    "def fill_nan(df):\n",
    "    for index, column in enumerate(df.columns[:9]):\n",
    "        df[column] = df[column].fillna(df.groupby('Potability')[column].transform('mean'))\n",
    "    return df\n",
    "\n",
    "# Wczytywanie danych\n",
    "df = pd.read_csv(\"water_potability.csv\")\n",
    "\n",
    "df = fill_nan(df)\n",
    "\n",
    "# Zrandomizowanie kolejności danych w datasecie\n",
    "df = df.sample(frac=1, random_state=10).reset_index(drop=True)\n",
    "\n",
    "# Podział na atrybuty i przewidywane wartości\n",
    "X, y = df.iloc[:, :-1], df.iloc[:, -1]\n",
    "\n",
    "# Normalizacja i skalowanie danych\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "sc = StandardScaler()\n",
    "X = sc.fit_transform(X.to_numpy())\n",
    "X = pd.DataFrame(X, columns=df.columns.values.tolist()[:-1])\n",
    "\n",
    "# Podział na dane trenujące i testowe, z uwzględnieniem równego rozłożenia danych\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1, stratify=y, random_state=1)\n",
    "\n",
    "print(X_train.shape, y_train.shape)\n",
    "print(X_test.shape, y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "id": "O82SGzK6tjN5"
   },
   "outputs": [
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       "      <th>3191</th>\n",
       "      <td>-0.587365</td>\n",
       "      <td>0.223203</td>\n",
       "      <td>-0.731867</td>\n",
       "      <td>0.397503</td>\n",
       "      <td>0.759893</td>\n",
       "      <td>0.330607</td>\n",
       "      <td>0.094379</td>\n",
       "      <td>0.282563</td>\n",
       "      <td>0.235024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.003078</td>\n",
       "      <td>-0.241037</td>\n",
       "      <td>0.773051</td>\n",
       "      <td>0.580019</td>\n",
       "      <td>1.334369</td>\n",
       "      <td>-0.049130</td>\n",
       "      <td>-1.121422</td>\n",
       "      <td>-0.200432</td>\n",
       "      <td>-0.946356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2068</th>\n",
       "      <td>-2.176058</td>\n",
       "      <td>1.443006</td>\n",
       "      <td>-1.626771</td>\n",
       "      <td>-4.164610</td>\n",
       "      <td>-0.033706</td>\n",
       "      <td>-1.050763</td>\n",
       "      <td>-0.391328</td>\n",
       "      <td>-0.398649</td>\n",
       "      <td>-0.298341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1484</th>\n",
       "      <td>0.213047</td>\n",
       "      <td>0.403036</td>\n",
       "      <td>-0.464729</td>\n",
       "      <td>0.070417</td>\n",
       "      <td>0.021560</td>\n",
       "      <td>-0.952776</td>\n",
       "      <td>-0.213330</td>\n",
       "      <td>0.111419</td>\n",
       "      <td>-0.235893</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>691</th>\n",
       "      <td>0.003078</td>\n",
       "      <td>1.199106</td>\n",
       "      <td>-0.003483</td>\n",
       "      <td>-0.670308</td>\n",
       "      <td>-0.069513</td>\n",
       "      <td>0.185754</td>\n",
       "      <td>-0.466010</td>\n",
       "      <td>0.031975</td>\n",
       "      <td>0.676276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1283</th>\n",
       "      <td>-2.034004</td>\n",
       "      <td>-1.508135</td>\n",
       "      <td>0.255310</td>\n",
       "      <td>0.083839</td>\n",
       "      <td>-1.413707</td>\n",
       "      <td>0.694074</td>\n",
       "      <td>-1.110579</td>\n",
       "      <td>0.232996</td>\n",
       "      <td>2.544703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2818</th>\n",
       "      <td>-0.702987</td>\n",
       "      <td>-0.575677</td>\n",
       "      <td>0.755056</td>\n",
       "      <td>0.664695</td>\n",
       "      <td>0.021560</td>\n",
       "      <td>-0.489334</td>\n",
       "      <td>0.371852</td>\n",
       "      <td>-2.272990</td>\n",
       "      <td>-1.764684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1330</th>\n",
       "      <td>1.525943</td>\n",
       "      <td>0.497074</td>\n",
       "      <td>-0.714355</td>\n",
       "      <td>-1.024237</td>\n",
       "      <td>-1.022037</td>\n",
       "      <td>-0.327074</td>\n",
       "      <td>-1.107341</td>\n",
       "      <td>0.517432</td>\n",
       "      <td>-1.230528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1926</th>\n",
       "      <td>-0.043558</td>\n",
       "      <td>-0.882359</td>\n",
       "      <td>-0.456141</td>\n",
       "      <td>-0.770271</td>\n",
       "      <td>0.795189</td>\n",
       "      <td>0.560306</td>\n",
       "      <td>-1.086081</td>\n",
       "      <td>-1.356820</td>\n",
       "      <td>0.172521</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2948 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ph  Hardness    Solids  Chloramines   Sulfate  Conductivity  \\\n",
       "1022  0.003078  0.688791  0.846257     1.428934 -0.858263      0.002792   \n",
       "3191 -0.587365  0.223203 -0.731867     0.397503  0.759893      0.330607   \n",
       "13    0.003078 -0.241037  0.773051     0.580019  1.334369     -0.049130   \n",
       "2068 -2.176058  1.443006 -1.626771    -4.164610 -0.033706     -1.050763   \n",
       "1484  0.213047  0.403036 -0.464729     0.070417  0.021560     -0.952776   \n",
       "...        ...       ...       ...          ...       ...           ...   \n",
       "691   0.003078  1.199106 -0.003483    -0.670308 -0.069513      0.185754   \n",
       "1283 -2.034004 -1.508135  0.255310     0.083839 -1.413707      0.694074   \n",
       "2818 -0.702987 -0.575677  0.755056     0.664695  0.021560     -0.489334   \n",
       "1330  1.525943  0.497074 -0.714355    -1.024237 -1.022037     -0.327074   \n",
       "1926 -0.043558 -0.882359 -0.456141    -0.770271  0.795189      0.560306   \n",
       "\n",
       "      Organic_carbon  Trihalomethanes  Turbidity  \n",
       "1022        0.913790         0.232417   2.319505  \n",
       "3191        0.094379         0.282563   0.235024  \n",
       "13         -1.121422        -0.200432  -0.946356  \n",
       "2068       -0.391328        -0.398649  -0.298341  \n",
       "1484       -0.213330         0.111419  -0.235893  \n",
       "...              ...              ...        ...  \n",
       "691        -0.466010         0.031975   0.676276  \n",
       "1283       -1.110579         0.232996   2.544703  \n",
       "2818        0.371852        -2.272990  -1.764684  \n",
       "1330       -1.107341         0.517432  -1.230528  \n",
       "1926       -1.086081        -1.356820   0.172521  \n",
       "\n",
       "[2948 rows x 9 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "a3jkTMFLtjN6"
   },
   "outputs": [],
   "source": [
    "# Trenowanie modelu klasyfikatora\n",
    "x = NaiveBayesClassifier()\n",
    "x.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "CoC22aNgtjN9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Predykcja wartości dla danych testowych\n",
    "predictions = x.predict(X_test)\n",
    "\n",
    "# Prawdopodobieństwa kolejnych predykcji\n",
    "probabilities = [p[1] for p in predictions]\n",
    "\n",
    "# Przewidziana wartość\n",
    "predictions = [p[0] for p in predictions]\n",
    "predictions[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "id": "JR06zodmtjN9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6280487804878049"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Wyliczenie accuracy modelu\n",
    "x.accuracy(y_test, predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "1jW0QPootjN_"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.14084507042253522"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import f1_score\n",
    "\n",
    "f1_score(y_test, predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "vEVogTmAtjOA"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.609756\n",
       "1    0.390244\n",
       "Name: Potability, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "id": "jCVOdBZytjOB"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x.visualize(y_test, predictions, 'Potability')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "aw8Tefprhjnn"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python3/dist-packages/matplotlib/cbook/__init__.py:1377: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "  x[:, None]\n",
      "/usr/lib/python3/dist-packages/matplotlib/axes/_base.py:237: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "  x = x[:, np.newaxis]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ph_val = X_test[\"ph\"]\n",
    "sulfate_val = X_test[\"Sulfate\"]\n",
    "hard_val = X_test[\"Hardness\"]\n",
    "carb_val = X_test[\"Organic_carbon\"]\n",
    "turb_val = X_test[\"Turbidity\"]\n",
    "ch_val = X_test[\"Chloramines\"]\n",
    "\n",
    "\n",
    "figure, axes = plt.subplots(nrows=3, ncols=2)\n",
    "\n",
    "axes[0, 0].plot(ph_val, predictions, 'bo')\n",
    "axes[0, 0].set_title(\"pH\")\n",
    "\n",
    "axes[0, 1].plot(sulfate_val, predictions, 'bo')\n",
    "axes[0, 1].set_title(\"Sulfate\")\n",
    "\n",
    "axes[1, 0].plot(hard_val, predictions, 'bo')\n",
    "axes[1, 0].set_title(\"Hardness\")\n",
    "\n",
    "axes[1, 1].plot(carb_val, predictions, 'bo')\n",
    "axes[1, 1].set_title(\"Organic carbon\")\n",
    "\n",
    "axes[2, 0].plot(turb_val, predictions, 'bo')\n",
    "axes[2, 0].set_title(\"Turbidity\")\n",
    "\n",
    "axes[2, 1].plot(ch_val, predictions, 'bo')\n",
    "axes[2, 1].set_title(\"Chloramines\")\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "naive_bayes.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}