{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TQqrOdkY6nsy"
   },
   "source": [
    "# **Klasyfikacja za pomocą naiwnej metody bayesowskiej z rozkładem normalnym**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "AlcfRFCPSXIj"
   },
   "source": [
    "# **Twierdzenie Bayesa**\n",
    "![bayes.svg](data:image/svg+xml;base64,PHN2ZyB4bWxuczp4bGluaz0iaHR0cDovL3d3dy53My5vcmcvMTk5OS94bGluayIgd2lkdGg9IjI3LjQ4NGV4IiBoZWlnaHQ9IjYuNTA5ZXgiIHN0eWxlPSJ2ZXJ0aWNhbC1hbGlnbjogLTIuNjcxZXg7IiB2aWV3Qm94PSIwIC0xNjUyLjUgMTE4MzMuMyAyODAyLjYiIHJvbGU9ImltZyIgZm9jdXNhYmxlPSJmYWxzZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIiBhcmlhLWxhYmVsbGVkYnk9Ik1hdGhKYXgtU1ZHLTEtVGl0bGUiPgo8dGl0bGUgaWQ9Ik1hdGhKYXgtU1ZHLTEtVGl0bGUiPntcZGlzcGxheXN0eWxlIHtcbWF0aHNmIHtQfX0oQVxtaWQgQik9e1xmcmFjIHt7XG1hdGhzZiB7UH19KEJcbWlkIEEpXCx7XG1hdGhzZiB7UH19KEEpfXt7XG1hdGhzZiB7UH19KEIpfX0sfTwvdGl0bGU+CjxkZWZzIGFyaWEtaGlkZGVuPSJ0cnVlIj4KPHBhdGggc3Ryb2tlLXdpZHRoPSIxIiBpZD0iRTEtTUpTUy01MCIgZD0iTTg4IDBWNjk0SDIzMFEzNDcgNjkzIDM3MCA2OTJUNDEwIDY4NlE0ODcgNjY3IDUzNSA2MTFUNTgzIDQ4NVE1ODMgNDA5IDUyNyAzNDhUMzc5IDI3NlEzNjkgMjc0IDI3OSAyNzRIMTkyVjBIODhaTTQ4NiA0ODVRNDg2IDUyMyA0NzEgNTUxVDQzMiA1OTNUMzkxIDYxMlQzNTcgNjIxUTM1MCA2MjIgMjY4IDYyM0gxODlWMzQ3SDI2OFEzNTAgMzQ4IDM1NyAzNDlRMzcwIDM1MSAzODMgMzU0VDQxNiAzNjhUNDUwIDM5MVQ0NzUgNDI5VDQ4NiA0ODVaIj48L3BhdGg+CjxwYXRoIHN0cm9rZS13aWR0aD0iMSIgaWQ9IkUxLU1KTUFJTi0yOCIgZD0iTTk0IDI1MFE5NCAzMTkgMTA0IDM4MVQxMjcgNDg4VDE2NCA1NzZUMjAyIDY0M1QyNDQgNjk1VDI3NyA3MjlUMzAyIDc1MEgzMTVIMzE5UTMzMyA3NTAgMzMzIDc0MVEzMzMgNzM4IDMxNiA3MjBUMjc1IDY2N1QyMjYgNTgxVDE4NCA0NDNUMTY3IDI1MFQxODQgNThUMjI1IC04MVQyNzQgLTE2N1QzMTYgLTIyMFQzMzMgLTI0MVEzMzMgLTI1MCAzMTggLTI1MEgzMTVIMzAyTDI3NCAtMjI2UTE4MCAtMTQxIDEzNyAtMTRUOTQgMjUwWiI+PC9wYXRoPgo8cGF0aCBzdHJva2Utd2lkdGg9IjEiIGlkPSJFMS1NSk1BVEhJLTQxIiBkPSJNMjA4IDc0UTIwOCA1MCAyNTQgNDZRMjcyIDQ2IDI3MiAzNVEyNzIgMzQgMjcwIDIyUTI2NyA4IDI2NCA0VDI1MSAwUTI0OSAwIDIzOSAwVDIwNSAxVDE0MSAyUTcwIDIgNTAgMEg0MlEzNSA3IDM1IDExUTM3IDM4IDQ4IDQ2SDYyUTEzMiA0OSAxNjQgOTZRMTcwIDEwMiAzNDUgNDAxVDUyMyA3MDRRNTMwIDcxNiA1NDcgNzE2SDU1NUg1NzJRNTc4IDcwNyA1NzggNzA2TDYwNiAzODNRNjM0IDYwIDYzNiA1N1E2NDEgNDYgNzAxIDQ2UTcyNiA0NiA3MjYgMzZRNzI2IDM0IDcyMyAyMlE3MjAgNyA3MTggNFQ3MDQgMFE3MDEgMCA2OTAgMFQ2NTEgMVQ1NzggMlE0ODQgMiA0NTUgMEg0NDNRNDM3IDYgNDM3IDlUNDM5IDI3UTQ0MyA0MCA0NDUgNDNMNDQ5IDQ2SDQ2OVE1MjMgNDkgNTMzIDYzTDUyMSAyMTNIMjgzTDI0OSAxNTVRMjA4IDg2IDIwOCA3NFpNNTE2IDI2MFE1MTYgMjcxIDUwNCA0MTZUNDkwIDU2Mkw0NjMgNTE5UTQ0NyA0OTIgNDAwIDQxMkwzMTAgMjYwTDQxMyAyNTlRNTE2IDI1OSA1MTYgMjYwWiI+PC9wYXRoPgo8cGF0aCBzdHJva2Utd2lkdGg9IjEiIGlkPSJFMS1NSk1BSU4tMjIyMyIgZD0iTTEzOSAtMjQ5SDEzN1ExMjUgLTI0OSAxMTkgLTIzNVYyNTFMMTIwIDczN1ExMzAgNzUwIDEzOSA3NTBRMTUyIDc1MCAxNTkgNzM1Vi0yMzVRMTUxIC0yNDkgMTQxIC0yNDlIMTM5WiI+PC9wYXRoPgo8cGF0aCBzdHJva2Utd2lkdGg9IjEiIGlkPSJFMS1NSk1BVEhJLTQyIiBkPSJNMjMxIDYzN1EyMDQgNjM3IDE5OSA2MzhUMTk0IDY0OVExOTQgNjc2IDIwNSA2ODJRMjA2IDY4MyAzMzUgNjgzUTU5NCA2ODMgNjA4IDY4MVE2NzEgNjcxIDcxMyA2MzZUNzU2IDU0NFE3NTYgNDgwIDY5OCA0MjlUNTY1IDM2MEw1NTUgMzU3UTYxOSAzNDggNjYwIDMxMVQ3MDIgMjE5UTcwMiAxNDYgNjMwIDc4VDQ1MyAxUTQ0NiAwIDI0MiAwUTQyIDAgMzkgMlEzNSA1IDM1IDEwUTM1IDE3IDM3IDI0UTQyIDQzIDQ3IDQ1UTUxIDQ2IDYyIDQ2SDY4UTk1IDQ2IDEyOCA0OVExNDIgNTIgMTQ3IDYxUTE1MCA2NSAyMTkgMzM5VDI4OCA2MjhRMjg4IDYzNSAyMzEgNjM3Wk02NDkgNTQ0UTY0OSA1NzQgNjM0IDYwMFQ1ODUgNjM0UTU3OCA2MzYgNDkzIDYzN1E0NzMgNjM3IDQ1MSA2MzdUNDE2IDYzNkg0MDNRMzg4IDYzNSAzODQgNjI2UTM4MiA2MjIgMzUyIDUwNlEzNTIgNTAzIDM1MSA1MDBMMzIwIDM3NEg0MDFRNDgyIDM3NCA0OTQgMzc2UTU1NCAzODYgNjAxIDQzNFQ2NDkgNTQ0Wk01OTUgMjI5UTU5NSAyNzMgNTcyIDMwMlQ1MTIgMzM2UTUwNiAzMzcgNDI5IDMzN1EzMTEgMzM3IDMxMCAzMzZRMzEwIDMzNCAyOTMgMjYzVDI1OCAxMjJMMjQwIDUyUTI0MCA0OCAyNTIgNDhUMzMzIDQ2UTQyMiA0NiA0MjkgNDdRNDkxIDU0IDU0MyAxMDVUNTk1IDIyOVoiPjwvcGF0aD4KPHBhdGggc3Ryb2tlLXdpZHRoPSIxIiBpZD0iRTEtTUpNQUlOLTI5IiBkPSJNNjAgNzQ5TDY0IDc1MFE2OSA3NTAgNzQgNzUwSDg2TDExNCA3MjZRMjA4IDY0MSAyNTEgNTE0VDI5NCAyNTBRMjk0IDE4MiAyODQgMTE5VDI2MSAxMlQyMjQgLTc2VDE4NiAtMTQzVDE0NSAtMTk0VDExMyAtMjI3VDkwIC0yNDZRODcgLTI0OSA4NiAtMjUwSDc0UTY2IC0yNTAgNjMgLTI1MFQ1OCAtMjQ3VDU1IC0yMzhRNTYgLTIzNyA2NiAtMjI1UTIyMSAtNjQgMjIxIDI1MFQ2NiA3MjVRNTYgNzM3IDU1IDczOFE1NSA3NDYgNjAgNzQ5WiI+PC9wYXRoPgo8cGF0aCBzdHJva2Utd2lkdGg9IjEiIGlkPSJFMS1NSk1BSU4tM0QiIGQ9Ik01NiAzNDdRNTYgMzYwIDcwIDM2N0g3MDdRNzIyIDM1OSA3MjIgMzQ3UTcyMiAzMzYgNzA4IDMyOEwzOTAgMzI3SDcyUTU2IDMzMiA1NiAzNDdaTTU2IDE1M1E1NiAxNjggNzIgMTczSDcwOFE3MjIgMTYzIDcyMiAxNTNRNzIyIDE0MCA3MDcgMTMzSDcwUTU2IDE0MCA1NiAxNTNaIj48L3BhdGg+CjxwYXRoIHN0cm9rZS13aWR0aD0iMSIgaWQ9IkUxLU1KTUFJTi0yQyIgZD0iTTc4IDM1VDc4IDYwVDk0IDEwM1QxMzcgMTIxUTE2NSAxMjEgMTg3IDk2VDIxMCA4UTIxMCAtMjcgMjAxIC02MFQxODAgLTExN1QxNTQgLTE1OFQxMzAgLTE4NVQxMTcgLTE5NFExMTMgLTE5NCAxMDQgLTE4NVQ5NSAtMTcyUTk1IC0xNjggMTA2IC0xNTZUMTMxIC0xMjZUMTU3IC03NlQxNzMgLTNWOUwxNzIgOFExNzAgNyAxNjcgNlQxNjEgM1QxNTIgMVQxNDAgMFExMTMgMCA5NiAxN1oiPjwvcGF0aD4KPC9kZWZzPgo8ZyBzdHJva2U9ImN1cnJlbnRDb2xvciIgZmlsbD0iY3VycmVudENvbG9yIiBzdHJva2Utd2lkdGg9IjAiIHRyYW5zZm9ybT0ibWF0cml4KDEgMCAwIC0xIDAgMCkiIGFyaWEtaGlkZGVuPSJ0cnVlIj4KIDx1c2UgeGxpbms6aHJlZj0iI0UxLU1KU1MtNTAiIHg9IjAiIHk9IjAiPjwvdXNlPgogPHVzZSB4bGluazpocmVmPSIjRTEtTUpNQUlOLTI4IiB4PSI2MzkiIHk9IjAiPjwvdXNlPgogPHVzZSB4bGluazpocmVmPSIjRTEtTUpNQVRISS00MSIgeD0iMTAyOSIgeT0iMCI+PC91c2U+CiA8dXNlIHhsaW5rOmhyZWY9IiNFMS1NSk1BSU4tMjIyMyIgeD0iMjA1NyIgeT0iMCI+PC91c2U+CiA8dXNlIHhsaW5rOmhyZWY9IiNFMS1NSk1BVEhJLTQyIiB4PSIyNjEzIiB5PSIwIj48L3VzZT4KIDx1c2UgeGxpbms6aHJlZj0iI0UxLU1KTUFJTi0yOSIgeD0iMzM3MyIgeT0iMCI+PC91c2U+CiA8dXNlIHhsaW5rOmhyZWY9IiNFMS1NSk1BSU4tM0QiIHg9IjQwNDAiIHk9IjAiPjwvdXNlPgo8ZyB0cmFuc2Zvcm09InRyYW5zbGF0ZSg1MDk2LDApIj4KPGcgdHJhbnNmb3JtPSJ0cmFuc2xhdGUoMTIwLDApIj4KPHJlY3Qgc3Ryb2tlPSJub25lIiB3aWR0aD0iNjIxOCIgaGVpZ2h0PSI2MCIgeD0iMCIgeT0iMjIwIj48L3JlY3Q+CjxnIHRyYW5zZm9ybT0idHJhbnNsYXRlKDYwLDc3MCkiPgogPHVzZSB4bGluazpocmVmPSIjRTEtTUpTUy01MCIgeD0iMCIgeT0iMCI+PC91c2U+CiA8dXNlIHhsaW5rOmhyZWY9IiNFMS1NSk1BSU4tMjgiIHg9IjYzOSIgeT0iMCI+PC91c2U+CiA8dXNlIHhsaW5rOmhyZWY9IiNFMS1NSk1BVEhJLTQyIiB4PSIxMDI5IiB5PSIwIj48L3VzZT4KIDx1c2UgeGxpbms6aHJlZj0iI0UxLU1KTUFJTi0yMjIzIiB4PSIyMDY2IiB5PSIwIj48L3VzZT4KIDx1c2UgeGxpbms6aHJlZj0iI0UxLU1KTUFUSEktNDEiIHg9IjI2MjIiIHk9IjAiPjwvdXNlPgogPHVzZSB4bGluazpocmVmPSIjRTEtTUpNQUlOLTI5IiB4PSIzMzczIiB5PSIwIj48L3VzZT4KIDx1c2UgeGxpbms6aHJlZj0iI0UxLU1KU1MtNTAiIHg9IjM5MjkiIHk9IjAiPjwvdXNlPgogPHVzZSB4bGluazpocmVmPSIjRTEtTUpNQUlOLTI4IiB4PSI0NTY4IiB5PSIwIj48L3VzZT4KIDx1c2UgeGxpbms6aHJlZj0iI0UxLU1KTUFUSEktNDEiIHg9IjQ5NTgiIHk9IjAiPjwvdXNlPgogPHVzZSB4bGluazpocmVmPSIjRTEtTUpNQUlOLTI5IiB4PSI1NzA4IiB5PSIwIj48L3VzZT4KPC9nPgo8ZyB0cmFuc2Zvcm09InRyYW5zbGF0ZSgyMDIwLC03NzEpIj4KIDx1c2UgeGxpbms6aHJlZj0iI0UxLU1KU1MtNTAiIHg9IjAiIHk9IjAiPjwvdXNlPgogPHVzZSB4bGluazpocmVmPSIjRTEtTUpNQUlOLTI4IiB4PSI2MzkiIHk9IjAiPjwvdXNlPgogPHVzZSB4bGluazpocmVmPSIjRTEtTUpNQVRISS00MiIgeD0iMTAyOSIgeT0iMCI+PC91c2U+CiA8dXNlIHhsaW5rOmhyZWY9IiNFMS1NSk1BSU4tMjkiIHg9IjE3ODgiIHk9IjAiPjwvdXNlPgo8L2c+CjwvZz4KPC9nPgogPHVzZSB4bGluazpocmVmPSIjRTEtTUpNQUlOLTJDIiB4PSIxMTU1NCIgeT0iMCI+PC91c2U+CjwvZz4KPC9zdmc+)"
   ]
  },
  {
   "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": {},
   "source": [
    "**Naiwny klasyfikator bayesowski jest naiwny, ponieważ zakłada, że poszczególne cechy są niezależne od siebie**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "SSaJsYOhz8h8"
   },
   "source": [
    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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>sepal.length</th>\n",
       "      <th>sepal.width</th>\n",
       "      <th>petal.length</th>\n",
       "      <th>petal.width</th>\n",
       "      <th>variety</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>Virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>Virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>Virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>Virginica</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal.length  sepal.width  petal.length  petal.width    variety\n",
       "0             5.1          3.5           1.4          0.2     Setosa\n",
       "1             4.9          3.0           1.4          0.2     Setosa\n",
       "2             4.7          3.2           1.3          0.2     Setosa\n",
       "3             4.6          3.1           1.5          0.2     Setosa\n",
       "4             5.0          3.6           1.4          0.2     Setosa\n",
       "..            ...          ...           ...          ...        ...\n",
       "145           6.7          3.0           5.2          2.3  Virginica\n",
       "146           6.3          2.5           5.0          1.9  Virginica\n",
       "147           6.5          3.0           5.2          2.0  Virginica\n",
       "148           6.2          3.4           5.4          2.3  Virginica\n",
       "149           5.9          3.0           5.1          1.8  Virginica\n",
       "\n",
       "[150 rows x 5 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "iris_data = pd.read_csv(\"iris.csv\")\n",
    "iris_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fd5194d9f40>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "setosa = iris_data[:50]\n",
    "versicolor = iris_data[50:100]\n",
    "virginica = iris_data[100:150]\n",
    "# ax.scatter(setosa['sepal.length'],np.arange(50), color='blue', lw=2)\n",
    "# ax.scatter(versicolor['sepal.length'],np.arange(50),  color='orange', lw=2)\n",
    "# ax.scatter(virginica['sepal.length'],np.arange(50),  color='green', lw=2) \n",
    "\n",
    "ax.scatter(setosa['petal.width'],np.arange(50), color='blue', lw=2)\n",
    "ax.scatter(versicolor['petal.width'],np.arange(50),  color='orange', lw=2)\n",
    "ax.scatter(virginica['petal.width'],np.arange(50),  color='green', lw=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ShapiroResult(statistic=0.9776989221572876, pvalue=0.4595281183719635)\n",
      "ShapiroResult(statistic=0.9778355956077576, pvalue=0.46473264694213867)\n",
      "ShapiroResult(statistic=0.9711798429489136, pvalue=0.25832483172416687)\n"
     ]
    }
   ],
   "source": [
    "from scipy import stats\n",
    "print(stats.shapiro(setosa['sepal.length']))\n",
    "print(stats.shapiro(versicolor['sepal.length']))\n",
    "print(stats.shapiro(virginica['sepal.length']))"
   ]
  },
  {
   "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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   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "v0oeHebytjNp"
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   "outputs": [],
   "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": 4,
   "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",
    "        \n",
    "        numerator = np.exp((-1/2)*((x-mean)**2) / (2 * var)) # Licznik wzoru na gęstość rozkładu normalnego \n",
    "        denominator = np.sqrt(2 * np.pi * var) # Mianownik wzoru na gęstość rozkładu normalnego \n",
    "        prob = numerator / denominator\n",
    "        \n",
    "        return prob\n",
    "    \n",
    "    def classify(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.classify(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], alpha=0.7, hue=target, dodge=False)\n",
    "        sns.countplot(x=target, data=pr, ax=ax[1], alpha=0.7, hue=target, dodge=False)\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(\"Predykcje\", fontsize=18)\n",
    "        plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pitność wody"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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": 6,
   "metadata": {
    "id": "O82SGzK6tjN5"
   },
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th>ph</th>\n",
       "      <th>Hardness</th>\n",
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       "      <td>0.232417</td>\n",
       "      <td>2.319505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <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": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "id": "a3jkTMFLtjN6"
   },
   "outputs": [],
   "source": [
    "# Trenowanie modelu klasyfikatora\n",
    "x = NaiveBayesClassifier()\n",
    "x.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "CoC22aNgtjN9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 8,
     "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": 9,
   "metadata": {
    "id": "JR06zodmtjN9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6280487804878049"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Wyliczenie accuracy modelu\n",
    "x.accuracy(y_test, predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "id": "1jW0QPootjN_"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.14084507042253522"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import f1_score\n",
    "\n",
    "f1_score(y_test, predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "vEVogTmAtjOA"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.609756\n",
       "1    0.390244\n",
       "Name: Potability, dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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": 13,
   "metadata": {
    "id": "aw8Tefprhjnn"
   },
   "outputs": [
    {
     "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",
    "figure.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fd5199264c0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "\n",
    "pca = PCA(n_components=2)\n",
    "pca.fit(X_test)\n",
    "X_pca = pca.transform(X_test)\n",
    "\n",
    "plt.scatter(X_pca[:, 0], X_pca[:, 1], c=predictions, s=50, cmap='viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fd51990eaf0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(X_pca[:, 0], X_pca[:, 1], c=y_test, s=50, cmap='viridis')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Irysy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(105, 4) (105,)\n",
      "(45, 4) (45,)\n",
      "0.9333333333333333\n"
     ]
    }
   ],
   "source": [
    "# Preprocessing danych\n",
    "\n",
    "\n",
    "# Wczytywanie danych\n",
    "df = pd.read_csv(\"iris.csv\")\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=0.3, stratify=y, random_state=1)\n",
    "\n",
    "print(X_train.shape, y_train.shape)\n",
    "print(X_test.shape, y_test.shape)\n",
    "\n",
    "\n",
    "# Trenowanie modelu klasyfikatora\n",
    "x = NaiveBayesClassifier()\n",
    "x.fit(X_train, y_train)\n",
    "\n",
    "\n",
    "# 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",
    "\n",
    "\n",
    "# Wyliczenie accuracy modelu\n",
    "print(x.accuracy(y_test, predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9326599326599326"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f1_score(y_test, predictions, average=\"macro\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fd519886fd0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pca = PCA(n_components=2)\n",
    "pca.fit(X_test)\n",
    "X_pca = pca.transform(X_test)\n",
    "\n",
    "df_pred = pd.DataFrame(predictions).replace({'Virginica': 0, 'Versicolor': 1, \"Setosa\": 2}, regex=True)\n",
    "df_pred = np.array(df_pred).reshape(1, -1)\n",
    "plt.scatter(X_pca[:, 0], X_pca[:, 1], c=df_pred[0], s=50, cmap='viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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dXY27uztvv/12a46LzdR+uZmQnM2Va+W4ONfcjVJSVkV3Nydix/oZ/QK0Yb/ubk6E+Hpy9GSB4XVt39q2e1LPotPpUatVBP7ByfAlsTkxrJwzrNGXyIN9upl1Q4Op+E3ta3sleYRhjtWdexFhPU3eoGBue2h6Tq7fltnkWMbmn1/vbkaXp6cXGNm6abfDHG8teXSQCbWnlm19yc5WbtUpulK15pLd7TInrKEjH7OOnDO3+pKdqfkgv24uhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFsGurDSUnJ/Phhx+i1+upqKjg/vvvZ82aNSbbX79+nS+//JLZs2e3VYjNWr8tkz2pZ9Hp9KjVKiLCejJnsr/RtvvTz5GQnM2Va+V0d3MixNeToycLDK9jx/oxMsgbgKdeTabwRqWhb2dHDc7ODkbbNjWug72aymodej1mx/eQbyeCgqx6uISVdYQcUrKGOVGbd6aWN8XUe4WpsZp6bzF3LICX1v/EsdNXDfEM9unGyjnDrHpcrNW+LpVer9dbFKUZCgoKiIqKIjExkR49eqDX68nOzqZ///4m+5w/f56YmBhSU1NvdXhGVVRUkJWVxYABA3B0dGT9tkx2H8pt1G7ckF6N3vT3p5/j/a3HqKjSmhzf0V7D3CmD2fhNVr1i1FRboNlxLY3PXqNi3rSAFk+c9i49PZ0gMytwwznRltpjDoFtj5k5jOWEo72G8OB7+D7tfKPlc6cMpgsFRueQqfeKwT7dOJlb1Ggs316u9YpHrXFDegGYNdbcKYPZeyTX6HjmFKXa/DB1XOZOGWz0vaK59s3NhzY5Q7py5Qp2dna4uroCoFKpDIl07NgxVq9eTWlpKQDz5s1j5MiRrFixghs3bhAdHY2TkxNbtmwhNzeXZcuWUVhYiJ2dHQsWLGD48OGUl5ezZMkSTp8+jZ2dHb179+bdd9/l8uXL/OUvf6G0tJSKigpGjBjB4sWLLdqHPalnTS5v+IafkJzdbNGoqNKSkJzdbDGq27b2/+ZoaXxVWj0Jydm3TUFqbzpCDimZsZyoqNIazkwaLk9IzuZPY7sZHcvUe4WxIlFRpTW6vKlxmhorITmby9fKW9ynOaaOi6n3CnPbN9QmBcnX15dBgwYxcuRIwsLCCAwMJDo6Go1GwyuvvMJHH32Ep6cnBQUFTJ48mV27drFs2TJiYmJISkoyjLNo0SKmTp3KlClTOH36NE888QTJycmkp6dTWlrK7t27ASguLgbgjjvuYMOGDXTu3Jmqqir++Mc/kpKSwvDhw1sce1ZWFkCjSVlLp9OTnp5eb5mpCdFQS9uZ27Yuc+K7fK28UduOrD3ta3vOIfg9j5TKVE6Yyvva9sbmkKk+5rJknObeJ8yZ8+np6Wa/V7T2vaVNCpJarWbdunWcOnWKo0ePsnfvXj799FMWL17M+fPn613jVqlU5Obm4ubmVm+MkpISsrOziYmJAcDHxwc/Pz8yMzPx9fUlJyeH5cuXExoaysiRIwHQarWsWrWKjIwM9Ho9V65c4eTJk2YlU+2ppXrLBaMTRK1WNTpt90i+2qIC4uHm1OJC4+HmBJhfmMyJz8PNyezLWO1Vay7Z2UJ7ziFA8ZfsTOWEWq0ymve1+WhsDpl6rzCXWq0CzCtMzb2ntHTO1+aHue8VzbVvLofa9C67vn378sQTT7Bx40a6dOmCXq+nX79+JCUlGf4dOHCAgQMHmjWut7c3u3bt4sEHH+TQoUNER0dTUVHBxo0buX79Olu3buWbb75hzJgxVFRUWBR7RFjPFi+PHeuHo72myfEc7TXEjvXDvYtDs9uubduScS2Nz16jInasn1lji7bXnnNIyYzlhKO9hoiwnkaXN5Urpt4rBvt0MzrWYB/jl/4iwnqaPVbsWD+T45la3hRTx8XU/pvbvqE2KUj5+flkZGQYXl+6dInCwkJ8fHzIzc3l8OHDhnXHjx9Hr9fj4uLCzZs3qa6uBsDFxQU/Pz8SExMByMnJ4eTJk/j7+3Pp0iU0Gg1jxozhr3/9K4WFhRQVFXHjxg08PDxwdHQkPz+f77//3uJ9mDPZn3FDehk+tajVKqM3DACMDPJm7pTBeLg5oaLm08G4Ib3qva79ku/vr45tVJQ6O2qMtm1uXEd7Naqa8MyOb3yoq3x/pGAdIYeUzFhOzJ0ymDmT/Y0ubypXTL1XrJwzzOhYK+cMM/neYu5YI4O8WTlnWKPiY+lddqaOi6n9N7d9Q21yl92FCxd4+eWXuXDhAp06dUKn0/HEE08wffp0jh8/zttvv01xcTFVVVV4e3uzYcMG1Go1L730Eunp6XTt2rXJL2QPHDhguP1Vp9MRFRXFM888w4ULF3j++ee5efMmXl5euLq6cu+99/LnP/+52Zjby91B1mLJJaz2rL3dZdcecwg6dh515Jy5VfvW3Hxok4LUHnXkRDKmIyeXMe2tILVXHfmYdeScsVVBkic1CCGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFsLggzZo1iy+++KLeMr1eT3h4ODNnziQtLc3sMX/++WcWLlzYbLv8/Hxmzpxp9vhCKInkkBD12VnaMSYmho0bNzJjxgzDstTUVNRqNQkJCahUqkZ9qqursbMzvcmBAweyZs2aZrft5eXF559/blngt7H96edISM7myrVyXJztASgpq6K7mxO9uqn4IPk7rlwrp7ubEyG+nhw9WWB4HTvWj5FB3kbHfWn9Txw7fdXwWqMGnY5m+9WNp7ubE3d1c+bn/ytEp9M3ajvYpxsr5wwzOs76bZnsST2LTqdHrVYREdaTOZP9zTw61h+rOZJDLdNwntSdU6bWmfo5WvLzbTi/a+firiOFrNiy0+hY/xW3l3MFpYY+3p6dWbdkjMl4m9rHtjqWSqDS6/WNs78FKisreeihh9i8eTN9+vQBYPHixfTu3ZuDBw/y9NNPM2rUKJYuXYpGo+HMmTOUlpaSlJTE2rVr2b17N66uroSGhnLo0CF27NhBamoqcXFx7Nixg/PnzxMTE8P06dM5cOAA5eXlvP766wQHBxvWpaamApCRkcGqVasoLS01xDFs2DDi4uI4cuQIVVVVuLm58cYbb3D33Xe3aP8qKirIyspiwIABODo6WnKIFGV/+jne33qMiiqtRf0d7TXMnTK40eRtmKwt7WdJPMaK0vptmew+lNuo7bghvZp8o0lPTycoKMissaw9Jzp6DkHr88jYPKmdU4DRdb69XI3OSW/PzvWKRK2m5oqp+e3exYHCG5VGx/o554rR7bh3caD0prZRvOHB9/B92nmj+2jNYtHUsWy4HWP5YQ3NzQeLL9k5ODgwfvx4tm/fDkBJSQl79+5l4sSJjdpmZ2fzySefkJSUxA8//MC+fftISkriyy+/JDe38RtAraKiIvz9/fn666/505/+xOrVq422mTt3Li+88AI7d+4kMTGRgQMHAjB79my2b9/Ozp07iYyMNNr/dpGQnG1xMQKoqNKSkJzdaHlTxaipfpbEY2xbe1LPGm1ranlTrDlWS0gONc/YPKmdU6bWmZqTxooENP3zNTWWsWJUO5ap7RTeqDQa757Usyb30ZqaOpZKYfElO4DJkycza9YsFi5cSHJyMoGBgdx5552N2kVERODs7AzUXJIYO3as4fWECRNYt26d0fGdnZ0ZNWoUAP7+/sTFxTVqk5mZSZ8+fQgMDARAo9HQtWtXAFJSUti8eTNlZWVUV1dbtI9ZWVkW9VOay9fKrTJGenq6VfpZGk/DcYxd3qtd3lys1hzLUrdDDoHleWRqnlhjPtey5s/X1ByypI+l+WZKU8fS2HZu1ZxvSqsKkq+vL56enqSkpLB9+3aeeuopo+1qE8dcDg4Ohv+r1WqzEuLChQu8+eabbNu2DW9vb/7973+zaNEis2PoKJfsPJKvtjqJPdycGp/Gbz5vUT9L42k4jnrLBaMJrVarmrzkYOySRHNj1V5usKbbIYfA8jwyNU883JwA6xSmJudKC+Z3w7HMLUqm+hjNt1Zo6lg23M6tvmRnSqtv+46JiSE+Pp7ffvuN8PDwZtuHhoby7bffUl5ejk6nY+fOna3avr+/Pzk5OWRkZACg1WopLi6mpKQEe3t7PDw80Ol0bNmypVXbae9ix/rhaK+xuL+jvYbYsX6Nlg/26WZRP0viMbatiLCeRtuaWt4Ua45lDskh04zNk9o5ZWqdqTnp7dnZ6PKmfr6mxnLv4mB0eURYT5Pbce/iYDTeiLCeJvfRmpo6lkrRqjMkgMjISOLi4pg6dWq9T2OmhIeHk5GRQVRUFF27dsXf35/i4mKLt+/q6kp8fDxvvfUWZWVlqNVqlixZwtChQ4mIiGDcuHG4ubkxYsQIs26jrb3Xo7LS+LXi9mbIAE9UDGDH/tMUFt+ks1PNj760vBr3rp2421XFhSI9hcU3ce/aiUF9unE856rh9aSRPjwwwJOKiop64778dAhrNqWRnXvNsEz9/+6ya6pfw3jcu3bCy9WJk+eK0Bv5tOjXy42FTwY3Gufp8X442Ok5kHkRvU6PSq1ihP9dPDnWr1Hbhswdq3YuWHgfkEkdNYeg9XlkbJ7UzinAxLoebEo+YeTn2N/EctNzxdj8rp2L7276iaxzNxuNBfDyhv8h72qZoU+Pbs689tyDHM7KMxpv/96uRvexuTlsrWNpbDvW3Hat5nLI4rvsWqOkpAQXFxd0Oh0vvvginp6eLFiwoK3DaNKNGzc4deqUrcMQCtS3b1+6dOli0xjaQw6B5JEwzlQO2aQg/elPf+LChQvcvHmT+++/n+XLl+Pi4tLWYTRJp9NRWlqKvb290d8HEbcfvV5PVVUVnTt3Rq227UNO2kMOgeSRqK+5HLJJQRJCCCEakmfZCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFaPWjg0T7dubMGZYuXUpRURGurq7ExcVx77332jqsW+batWssXryYs2fP4uDgQK9evVixYgXu7u62Dk20Ex01Z5SQG/KLsbe52NhYYmJiiI6OJikpie3bt5OQkGDrsG6ZoqIifvnlF8LCwgCIi4ujuLiYN954w8aRifaio+aMEnJDLtndxq5evcqJEyeIjIwEah7yeeLECQoLC20c2a3j6upqSDioedL1xYsXbRiRaE86cs4oITekIN3G8vLy8PLyQqOpeSS9RqPB09OTvLw8G0fWNnQ6HV988QWjR4+2dSiinbhdcsZWuSEFSdy2XnvtNZydnXnyySdtHYoQimKr3JCbGm5jPXr0ID8/H61Wi0ajQavVUlBQQI8ePWwd2i0XFxdHbm4uGzZssPmTu0X7cTvkjC1zQzLxNtatWzf8/PzYtWsXALt27cLPz6/D33H2zjvvkJWVxQcffNCiP4gnRK2OnjO2zg25y+42l5OTw9KlS7l+/Tp33HEHcXFx/OEPf7B1WLfMr7/+SmRkJPfeey+dOnUC4J577uGDDz6wcWSiveioOaOE3JCCJIQQQhHkkp0QQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQgCSGEUAQpSEIIIRRBCpIQQghFkIIkhBBCEaQg3ebi4+NZtGiR0XWpqakMHz68jSOq0VRcQiiZNebuzp07efrpp02unzlzJlu3bjW5funSpaxdu7ZVMdiCFCSFGj16NIMGDSIgIIChQ4eydOlSSktLm+3X3ERVIlsWPnH7aE85FRUVxd/+9rcWtd2xYwczZsy4xRG1DSlICrZhwwYyMjJITEwkKyuL9evX2zokIdo1ySllk4LUDnh5efHQQw/x66+/ApCZmcn06dMJDg4mKiqK1NRUANauXUtaWhorVqwgICCAFStWALBy5UpGjBhBYGAgkyZNIi0tzaI48vPz+fOf/8wDDzzA6NGjSUhIMKyLj4/n+eefZ/HixQQEBPDYY4/x888/G9b/7//+LxMmTCAgIIB58+Yxf/581q5dS1lZGbNnz6agoICAgAACAgLIz88HoKqqyuR4QrSGrXLqySef5NtvvwUgPT2dfv36sX//fgAOHTpEdHQ00Pis53/+53+IiIggKCiIFStWUPuHvnNycnjllVfIzMwkICCA4OBgQ5/r16/zzDPPEBAQwJQpUzh79mwrjljbkILUDuTl5ZGSkoKfnx/5+fk8++yzzJkzhyNHjrBkyRLmzZtHYWEhCxYsIDg4mGXLlpGRkcGyZcsAGDhwIF9//TVHjhwhMjKS559/noqKCrNi0Ol0zJkzh379+pGSksLf//53/v73v/Pjjz8a2vzwww889thjpKWlMXr0aF577TUAKisrmTt3LhMnTjTEsHfvXgCcnZ35+OOP8fT0JCMjg4yMDLy8vJocT4jWslVOhYSEcOTIEQCOHj2Kt7c3R48eBeDIkSOEhIQ06lNYWMjcuXOZP38+hw8fpmfPnvz73/8GoE+fPixfvhx/f38yMjLqFcbdu3czd+5cjh49Ss+ePdvFd0pSkBTsT3/6E8HBwTz++OOEhITw3HPPkZSUxPDhwxkxYgRqtZoHH3yQAQMGcODAAZPjREdH4+bmhp2dHU8//TSVlZWcOXPGrFh+/vlnQ2I4ODjg7e3N1KlT2b17t6FNUFAQI0aMQKPREB0dzcmTJwE4duwY1dXVxMbGYm9vzyOPPMLAgQOb3aap8YSwlK1zKjQ0tF5BevbZZw0F6ejRo4SGhjbqk5KSwn333UdERAT29vY89dRTdO/evdltjRkzhkGDBmFnZ0dUVBTZ2dnN9rE1O1sHIEz74IMPGDp0aL1lFy9eZM+ePezbt8+wrLq6mrCwMJPjfPrpp2zbto2CggJUKhUlJSVcu3bNrFguXLhAQUFBvUsCWq223uu6SdKpUycqKiqorq6moKAALy8vVCqVYX2PHj2a3aap8ezsZNoKy9g6p/z9/fntt9+4cuUKJ0+eZP369bz33nsUFhZy/PjxevlUq6CggDvvvNPwWqVSWZQ/ZWVlzfaxNcnsdqZHjx5ER0ezcuXKFrVPS0vjk08+4bPPPuO+++5DrVYTEhJiuAZtznbvuecevvvuO7Nj9vDwID8/H71ebyhKeXl5eHt7A9QrVEK0tbbMKScnJ+6//34SEhK47777cHBwICAggM8++4yePXvi7u7eqI+HhweXLl0yvNbr9eTl5Rled6T8kUt27UxUVBT79u3jxx9/RKvVUlFRQWpqqmHCdu/enXPnzhnal5aWotFocHd3p7q6mvfff5+SkhKztzto0CA6d+7MRx99xM2bN9FqtZw6dYrjx48329ff3x+NRsOmTZuorq5m79699W5Q6NatG0VFRdy4ccPsuIRorbbOqdDQUDZt2mT4vigsLKze64ZGjBjBr7/+ynfffUd1dTUJCQlcuXLFsL5bt27k5+dTWVlpye4rihSkdqZHjx6sW7eODz/8kCFDhjBixAg+/fRTdDodALGxsXz77beEhISwcuVKhg0bxkMPPcSjjz7K6NGjcXR0bNHpfkMajYYNGzZw8uRJwsPDeeCBB3jppZdalIgODg7Ex8ezbds2QkJC2LlzJyNHjsTBwQGo+WL2scceY8yYMQQHBxvushOiLbR1ToWEhFBaWmooQA1fN+Tu7s67777LmjVrCAsLIzc3l8DAQMP6Bx54AB8fH4YNG9bkZcb2QKU399qNEFYwZcoUpk+fTkxMjK1DEUIohJwhiTZx5MgRLl++THV1NYmJifzyyy889NBDtg5LCKEgclODaBNnzpxh/vz5lJeXc8899/Dee+/h6elp67CEEAoil+yEEEIogpwhmaDT6SgtLcXe3r5D3VYpLKfX66mqqqJz586o1XK1uyUkj0RdzeWQFCQTSktLOXXqlK3DEArUt29funTpYusw2gXJI2GMqRxqsiDNmjWL8PDweg/50+v1jBkzhjfffNPoYy5aKj8/n0WLFvH5559b1P/8+fPExMQYHoJobfb29kDNgau9PdmasrKyGDBggFXGOpyVx479pyksvol7105MGunDAwPMv7U7KyuLzHNqDmReRK/7/UquSq1Cr9M3Grvuduu2vdPNiUvXyls0RktistZxaq3KykpOnTplmBstJXlknTxq67lgLK+ARstOn7tmyBmVWsUI/7sAGi17cmx/NiWfaLQ8/2oZ2bm/P+XBr5cbD/rfbZWcrksJudRcDjVZkGJiYti4cWO9REpNTTX8ZnJzdDodKpXK6Km6l5eXxUnUGlqtFo1G02y72pgdHBxwdHS8JbFYY9z96ed4f2sWFVVaAIpKS4nfmoUeDSODvM0aa9eRQtJOm368SN2xgXrbretaE7/gakl8t+r4W8rcS0+SR9bLo7aaC8by6v/78jh6PWj/3wetotJS1nxxjIbfwn/9Y+Onan/941nSf7nKuYLSZtseOnGFQyd+/8XX1uR0Q0rJJVM51OSF8PDwcHJzc8nJyTEs27FjB5MmTeLjjz9m8uTJTJw4keeee47Lly8DNX+GYN68eTz99NOMGzeOoqIiXn31VSIiIoiKimL69OlAzSezur/ElZGRwYwZM4iKiiIqKoqffvoJgOPHjzNt2jTGjx/PtGnTTD4ZICUlhQkTJjB+/HieeuopcnNzgZrEHz9+PH/961+Jjo4mJSWlpcesXUhIzm5UFCqqtCQkm/8gxfSc5p91VTu2se22lKXxtVeSR+2PsfldrdUbilEtc24Ja1iMzHG75EyTZ0gODg6MHz+e7du3s3jxYkpKSti7dy+vvPIKaWlpfPXVV6jVajZv3sxbb73FmjVrgJrJv2PHDtzd3Tlx4gSpqans3r0btVpNcXFxo+0UFRUxd+5c4uPjCQwMRKvVUlJSQmVlJfPmzePNN99kyJAhHDx4kHnz5jV6ntrVq1dZvHgxmzZtwsfHh61bt7Jo0SLDX3k8ffq04e+ZmCsrK8vsPi2Vnp7e6jEuXys3udzc8VuaXKa2aQ5z4rPGcbIlySPr5VFbzQVrzHFrsySnG1J6LjV7U8PkyZOZNWsWCxcuJDk5mcDAQH744QeysrKYOHEiUHP67uLiYugzfPhww0MCvb29qa6u5sUXXyQsLIxRo0Y12kZmZiZ9+vQxPA5Do9HQtWtXfvnlF+zt7RkyZAgAQ4cOxd7enjNnztC5c2dD/2PHjuHr64uPT8013piYGJYvX254rE2vXr0sSiKAAQMG3JLT3PT0dIKCglo9jkfyVaPJ4+HmZPb4qi/Ot6goebg5Aa1L2pbGZ63jZA0VFRUWv7FKHrU+j9pyLpjKK1uyJKfrUkIuNZdDzd676uvri6enJykpKWzfvp2YmBj0ej1z5swhKSmJpKQkdu3axZYtWwx96k7yLl268M9//pNx48bxyy+/8NhjjxkuS7QVZ2fnNt1eW4od64ejff1r+Y72GmLH+pk9VlCf5o9T7djGtttSlsbXnkketS/G5redRoVGXf+7D3O+TvT27Nx8IxNul5xp0S9TxMTEEB8fz2+//UZ4eDijR49m8+bNhssGlZWVJv94WmFhIeXl5Tz00EMsWrSILl261HtyLtQ8DTonJ4eMjAyg5pNicXExvXv3pqqqisOHDwM1f+K3urqa3r17N+p/8uRJwzX6xMRE+vfvX+/TZkc1MsibuVMG4+HmhIqaT1Fzpwy26MvPyFB3xg3phbpB0tW+rjt23e02bOvt2blFY9xuJI/aD2N59fy0AOZPD6i37C8zAuvljFqtYtyQXkaXrVsyxujywT7d6m17sE83Fj4eaJWcbm9a9HtIkZGRxMXFMXXqVBwcHJgwYQJFRUU8+eSTQM0trDNmzMDX17dR37y8PF5++WWqq6vRarUMHz4cf39/Ll68aGjj6upKfHw8b731FmVlZajVapYsWcLQoUN57733eP311ykrK8PZ2Zl333230e2j7u7urFq1ikWLFlFdXY27uztvv/12a45Lu1JbIKxhzmR/5kz2b/Pt3g4kj9oXU/O74bKRQd7Mmezf6JKYsTwyN79uN/LoIBNqr3Uq/Tska5KYmnar50RHZM1jpqS5YIzE17zm5oM8/0QIIYQiSEESQgihCFKQhBBCKIIUJCGEEIogBUkIIYQiSEESQgihCFKQhBBCKIIUJCGEEIogBUkIIYQiSEESQgihCFKQhBBCKIIUJCGEEIogBUkIIYQiSEESQgihCFKQhBBCKIIUJCGEEIogBUkIIYQiSEESQgihCFKQhBBCKIIUJCGEEIogBUkIIYQiSEESQgihCFKQhBBCKIIUJCGEEIogBUkIIYQiSEESQgihCFKQhBBCKIIUJCGEEIogBUkIIYQiSEESQgihCFKQhBBCKEKbFaTk5GQmTJhAdHQ0ERERLFy4sMn2169f5+OPP26j6IRQPskh0dHZtcVGCgoKWL58OYmJifTo0QO9Xk92dnaTfa5fv84nn3zC7Nmz2yLEFlm/LZM9qWfR6fQtaq9Wq4gI68mcyf7sTz9HQnI2V66V093NiYd8OxEUdIsDFh1GR8khgPELkxot+2ZNdKNldfNNrVYR+AcnkznTML9ix/oxMsjb2qGLW6xNCtKVK1ews7PD1dUVAJVKRf/+/QE4duwYq1evprS0FIB58+YxcuRIVqxYwY0bN4iOjsbJyYktW7aQm5vLsmXLKCwsxM7OjgULFjB8+HDKy8tZsmQJp0+fxs7Ojt69e/Puu+9y+fJl/vKXv1BaWkpFRQUjRoxg8eLFFu3D+m2Z7D6Ua1YfnU7P7kO5XLhcwsncIiqqtABcvlbON0du0rv3OUka0SIdIYfAeDGqXV63KDXMN51OT9rpMtZvy2TOZP96ffenn+P9rcfq5df7W48BSH61M21SkHx9fRk0aBAjR44kLCyMwMBAoqOj0Wg0vPLKK3z00Ud4enpSUFDA5MmT2bVrF8uWLSMmJoakpN8n8KJFi5g6dSpTpkzh9OnTPPHEEyQnJ5Oenk5paSm7d+8GoLi4GIA77riDDRs20LlzZ6qqqvjjH/9ISkoKw4cPN3sf9qSetXj/j52+2mhZlVZPQnK2JIxokY6QQ+YwlW97Us82KkgJydmGYlSrokor+dUOtUlBUqvVrFu3jlOnTnH06FH27t3Lp59+yuLFizl//ny9SwoqlYrc3Fzc3NzqjVFSUkJ2djYxMTEA+Pj44OfnR2ZmJr6+vuTk5LB8+XJCQ0MZOXIkAFqtllWrVpGRkYFer+fKlSucPHnSrGTKysoCaPFlOnNcvlZOenq61cdtDaXFA8qMqa215xyC3/OoKXV/zqbyTafTN5oPl6+VG21ri/xS+lxVenxtUpBq9e3bl759+/LEE08wbtw49Ho9/fr14x//+EejtufPn2/xuN7e3uzatYvDhw+TkpLC2rVr+eabb9i4cSPXr19n69atODo68vLLL1NRUWFWzAMGDMDR0RH1lgtWL0oebk4EKeiLpPT0dEXFA8qKqaKiokVvrLdSe8wh+D2P2Gw6pro/Z1P5plarGs0Hj+SrRotSW+eXkuaqMUqIr7kcapO77PLz88nIyDC8vnTpEoWFhfj4+JCbm8vhw4cN644fP45er8fFxYWbN29SXV0NgIuLC35+fiQmJgKQk5PDyZMn8ff359KlS2g0GsaMGcNf//pXCgsLKSoq4saNG3h4eODo6Eh+fj7ff/+9xfsQEdbT4r6DfbrhaK+pt8xeoyJ2rJ/FY4rbS0fIIXOYyjdjy2PH+jXKL0d7jeRXO9QmZ0jV1dXEx8dz4cIFOnXqhE6nY/78+fTv359169bx9ttv88Ybb1BVVYW3tzcbNmzA1dWV8ePHM378eLp27cqWLVtYvXo1y5Yt47PPPsPOzo5Vq1bh7u7OgQMHWLNmDQA6nY5nnnkGLy8vZs6cyfPPP09kZCReXl4MGTLE4n2ovW5tzbvs5Pq2aKmOkENQczddS+6ya5hvtXfZNfz+CH6/cUHusmv/VHq93vpfjnQAtaeWhksNVqaE0+eGJKam3eo50RFZ85gpaS4YI/E1r7n5IE9qEEIIoQhSkIQQQiiCFCQhhBCKIAVJCCGEIkhBEkIIoQhSkIQQQiiCFCQhhBCKIAVJCCGEIkhBEkIIoQhSkIQQQiiCFCQhhBCKIAVJCCGEIkhBEkIIoQhSkIQQQiiCFCQhhBCKIAVJCCGEIkhBEkIIoQhSkIQQQiiCFCQhhBCKIAVJCCGEIkhBEkIIoQhSkIQQQiiCFCQhhBCKIAVJCCGEIkhBEkIIoQhSkIQQQiiCFCQhhBCKIAVJCCGEIkhBEkIIoQhSkIQQQiiCFCQhhBCKIAVJCCGEIthZ2nHWrFmEh4czY8YMwzK9Xs+YMWO46667eP755wkODjZrzJ9//pnPPvuMNWvWNNkuPz+fRYsW8fnnn1sUu2gb+9PPkZCczeVr5ajVKnQ6PY72aiqrdej19dsO9unGyjnDjPZh8/l6bWuXd3G2B+BGWVW9dRFhPZkz2b/F8V25Vk53Nydix/oBNFo2Msi7dQfCBMkhYcr6bZnsST2LTqc3zGm/3t2Mzs2X1v/EsdNXDX1rc6mh42dK+SD5u3r99x7JNdrXWG58tfcXzhWUGtp6e3ZmYJ/uLY6zJVR6fcO3hpZJTk5m48aNfPXVV4Zlhw8f5uWXX+a7775DpVI16lNdXY2dncU1sE1VVFSQlZXFgAEDcHR0tPr46enpBAUFWX3c1rBmTPvTz/H+1mNUVGlb3MfbszMF126a1ceUcUN6NVmUjMWnUatQqaBa+3tKONprmDtlMCODvK0+Jzp6DoF180iJOVOXteJbvy2T3YdyGy1Xqaj3Qc7RXoOnW6d6RaJWw6K0P/0c732ZQZW2+bf71uah4YNknThbmkMWX7ILDw8nNzeXnJwcw7IdO3YwadIkYmNj2bdvHwBLly7lxRdf5PHHHycmJgaAtWvX8vDDDzNlyhTefvttJk2aBEBqaqrh/+fPnycsLIy1a9cyYcIEHn30UdLS0uqtq5WRkcGMGTOIiooiKiqKn376CYC4uDhiYmKIioriqaee4sKFC5burjBTQnK22RP6XEGpVYoRwJ7Us02uNxafVqevV4wAKqq0JCRnWyWmhiSHhDGm5m7DU4eKKq3RYgTUO+uBmvnekmIErc/DusUIzMshiz9qOTg4MH78eLZv387ixYspKSlh79697N69m4MHD9Zrm52dzaZNm3B2duaHH35g3759JCUl0alTJ+bNm2dyG0VFRfj7+7NgwQJ27tzJ6tWr2bJlS6M2c+fOJT4+nsDAQLRaLSUlJQDMnj2bJUuWALB161ZWr17N2rVrzdrPrKwss9qbIz09/ZaNbSlrxXT5WrlVxrGUTqdvcl/Mie/ytfJb8rO6XXIIrJdHSsyZuqwRX8M3dEvVjcXW+djSHGrVuf/kyZOZNWsWCxcuJDk5mcDAQO68885G7SIiInB2dgZqPsGNHTvW8HrChAmsW7fO6PjOzs6MGjUKAH9/f+Li4hq1yczMpE+fPgQGBgKg0Wjo2rUrACkpKWzevJmysjKqq6st2ke5ZGcZj+SrNk0CtVrV5L6YE5+HmxNBQUGGyw3WdDvkEFgnj5SYM3VZKz71lgtWKUp1Y7F1PrY0h1p1l52vry+enp6kpKSwfft2w+WEhmoTx1wODg6G/6vVarMS4sKFC7z55pusWbOGXbt28cYbb1BZWWlRHMJ8sWP9cLTXmNXH27Oz2X1MiQjr2eR6Y/Fp1CrsNPW/t3G01xhudrgVJIdEQ6bmbsOvFB3tNXh7djbadrBPt3qvY8f6Ya9p/J2kMa3NQ7Xa8hxq9bejMTExxMfHc/HiRcLDw5ttHxoaSnx8PP/xH/+Bo6MjO3fubNX2/f39ycnJISMjg4CAAMPlhpKSEuzt7fHw8ECn0zW6TNGc2ns9bmUCVlRU3LKxLWWtmIYM8ETFAHbsP01h8U1UahV6nR4HOzWVWh00+ADo18uNhU8Gczgrr1GfhmqXd3aqmb6l5dX11o3wv4snx/o1uS8N43Pv2olJI30AGi17YIAnFRUVhrlg4X1AJnXUHALr55ESc6Yua8T39Hg/HOz0HMi8iF6nN8xpH283I3OzB2s2pZGde83QvzaX6sYyZIAn58+5cTSnol7//8m8YLRv3TysbfvPn/6PvKtlhrY9ujnTr5dbC+NsWQ61uiBFRkYSFxfH1KlT630aMyU8PJyMjAyioqLo2rUr/v7+FBcXW7x9V1dX4uPjeeuttygrK0OtVrNkyRKGDh1KREQE48aNw83NjREjRhi+0G2JqqqaW4lPnTplcWzNuZXfT1nKmjG5ALEj3czatrl9jNO1aD8ab6vmi+CGy7Ky6n9BXFVVRadOnVoZ4+86ag6B9fNIiTlTl7Xi8/cGf++6l251wFWjc/NR/0486t+j2Tj8vJ3x8657pm26r7HcmDasK9C1wai6FsdZl6kcsvi279YoKSnBxcUFnU7Hiy++iKenJwsWLGjrMJqk0+koLS3F3t7e6O234vaj1+upqqqic+fOqNW2/Z3y9pBDIHkk6msuh2zyCw1LlizhwoUL3Lx5k/vvv5/Zs2fbIowmqdVqunTpYuswhMJY88yoNdpDDoHkkWisqRyyyRmSEEII0ZA8y04IIYQiSEESQgihCFKQhBBCKIIUJCGEEIogBUkIIYQiSEESQgihCFKQbCgpKYnx48fTv39/Nm3aZLM4zpw5w7Rp03j00UeZNm0av/32m81iqRUXF8fo0aPp16/fLX1ahmhflJIzdSkxf+pqT7kkBcmG/Pz8WLt2LZGRkTaN45VXXuHxxx/n22+/5fHHH2fZsmU2jQdqHo/zj3/8g7vvvtvWoQgFUUrO1KXE/KmrPeWSFCQb6tu3Lz4+PjZ9DM3Vq1c5ceKEIcEjIyM5ceIEhYWFNosJIDg4mB49ejTfUNxWlJAzdSk1f+pqT7mkjJ+qsJm8vDy8vLzQaGoeN6/RaPD09CQvL8/GkQmhfJI/1mWTZ9ndLiZOnMjFixeNrjt48KBhEgshakjO3N6kIN1CiYmJtg6hWT169CA/Px+tVotGo0Gr1VJQUNBuTvFFx9IecqYuyR/rkkt2t7lu3brh5+fHrl27ANi1axd+fn64u7vbODIhlE/yx7rkad82tGvXLlatWsX169ext7fHycmJv/3tb/j4+LRpHDk5OSxdupTr169zxx13EBcXxx/+8Ic2jaGhlStX8t1333HlyhXc3NxwdXXln//8p01jEranlJypS4n5U1d7yiUpSEIIIRRBLtkJIYRQBClIQgghFEEKkhBCCEWQgiSEEEIRpCAJIYRQBClIQgghFEEKkhBCCEWQgiSEEEIR/n/T4Jax/iNlPwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sep_len = X_test[\"sepal.length\"]\n",
    "sep_with = X_test[\"sepal.width\"]\n",
    "pet_len = X_test[\"petal.length\"]\n",
    "pet_with = X_test[\"petal.width\"]\n",
    "\n",
    "figure, axes = plt.subplots(nrows=2, ncols=2)\n",
    "\n",
    "axes[0, 0].plot(sep_len, predictions, 'bo')\n",
    "axes[0, 0].set_title(\"Sepal lenght\")\n",
    "\n",
    "axes[0, 1].plot(sep_with, predictions, 'bo')\n",
    "axes[0, 1].set_title(\"Sepal width\")\n",
    "\n",
    "axes[1, 0].plot(pet_len, predictions, 'bo')\n",
    "axes[1, 0].set_title(\"Petal length\")\n",
    "\n",
    "axes[1, 1].plot(pet_with, predictions, 'bo')\n",
    "axes[1, 1].set_title(\"Petal width\")\n",
    "\n",
    "figure.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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