Sugarbeet-MultiRegression_v1_kulleme_p1_p2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "21a3ae81",
   "metadata": {},
   "source": [
    "# Sugar-Beet-MultiRegression_Kullenme_p1+p2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e61e2032",
   "metadata": {},
   "source": [
    "## Kllm_MS_TE_RGB_train_p1_p2.csv   +  Kllm_MS_TE_RGB_test_p1_p2.csv.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "617d0fce",
   "metadata": {},
   "source": [
    "## KULLEME"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ae12ed0f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importing the libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f01fa297",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = pd.read_csv('Kllm_MS_TE_RGB_train_p1_p2.csv', sep=';', header=None)\n",
    "df_test = pd.read_csv('Kllm_MS_TE_RGB_test_p1_p2.csv', sep=';', header=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "279cf1d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = df_train.iloc[1:]\n",
    "df_test = df_test.iloc[1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fc79c852",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train.rename(columns = {0:'Id'}, inplace = True)\n",
    "\n",
    "df_train.rename(columns = {1:'Green_MS'}, inplace = True)\n",
    "df_train.rename(columns = {2:'Yellow_MS'}, inplace = True)\n",
    "df_train.rename(columns = {3:'Orange1_MS'}, inplace = True)\n",
    "df_train.rename(columns = {4:'Orange2_MS'}, inplace = True)\n",
    "df_train.rename(columns = {5:'Red_MS'}, inplace = True)\n",
    "\n",
    "df_train.rename(columns = {6:'Yellow_TE'}, inplace = True)\n",
    "df_train.rename(columns = {7:'Orange_TE'}, inplace = True)\n",
    "df_train.rename(columns = {8:'Cyan_TE'}, inplace = True)\n",
    "df_train.rename(columns = {9:'Dblue_TE'}, inplace = True)\n",
    "df_train.rename(columns = {10:'Black_TE'}, inplace = True)\n",
    "\n",
    "df_train.rename(columns = {11:'Green_RGB'}, inplace = True)\n",
    "df_train.rename(columns = {12:'Yellow_RGB'}, inplace = True)\n",
    "df_train.rename(columns = {13:'Orange1_RGB'}, inplace = True)\n",
    "df_train.rename(columns = {14:'Orange2_RGB'}, inplace = True)\n",
    "df_train.rename(columns = {15:'Red_RGB'}, inplace = True)\n",
    "\n",
    "df_train.rename(columns = {16:'Sicaklik_Ort'}, inplace = True)\n",
    "df_train.rename(columns = {17:'Sicaklik_Max'}, inplace = True)\n",
    "df_train.rename(columns = {18:'Sicaklik_Min'}, inplace = True)\n",
    "\n",
    "df_train.rename(columns = {19:'Nem_Ort'}, inplace = True)\n",
    "df_train.rename(columns = {20:'Nem_Max'}, inplace = True)\n",
    "df_train.rename(columns = {21:'Nem_Min'}, inplace = True)\n",
    "\n",
    "df_train.rename(columns = {22:'Yagis'}, inplace = True)\n",
    "\n",
    "df_train.rename(columns = {23:'Ilaclama'}, inplace = True)\n",
    "\n",
    "df_train.rename(columns = {24:'Kulleme'}, inplace = True)\n",
    "\n",
    "df_train.rename(columns = {25:'Tarih'}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "624d8878",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>Green_MS</th>\n",
       "      <th>Yellow_MS</th>\n",
       "      <th>Orange1_MS</th>\n",
       "      <th>Orange2_MS</th>\n",
       "      <th>Red_MS</th>\n",
       "      <th>Yellow_TE</th>\n",
       "      <th>Orange_TE</th>\n",
       "      <th>Cyan_TE</th>\n",
       "      <th>Dblue_TE</th>\n",
       "      <th>...</th>\n",
       "      <th>Sicaklik_Ort</th>\n",
       "      <th>Sicaklik_Max</th>\n",
       "      <th>Sicaklik_Min</th>\n",
       "      <th>Nem_Ort</th>\n",
       "      <th>Nem_Max</th>\n",
       "      <th>Nem_Min</th>\n",
       "      <th>Yagis</th>\n",
       "      <th>Ilaclama</th>\n",
       "      <th>Kulleme</th>\n",
       "      <th>Tarih</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>16,90465002</td>\n",
       "      <td>37,99807254</td>\n",
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       "      <td>5,255775212</td>\n",
       "      <td>11,38044948</td>\n",
       "      <td>17,7683399</td>\n",
       "      <td>26,38964786</td>\n",
       "      <td>29,13040372</td>\n",
       "      <td>...</td>\n",
       "      <td>24,43</td>\n",
       "      <td>34,83</td>\n",
       "      <td>14,46</td>\n",
       "      <td>55,31</td>\n",
       "      <td>99,99</td>\n",
       "      <td>16,83</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>17,64092354</td>\n",
       "      <td>34,05604382</td>\n",
       "      <td>21,41426875</td>\n",
       "      <td>11,13525907</td>\n",
       "      <td>6,622319315</td>\n",
       "      <td>10,96859475</td>\n",
       "      <td>19,13446622</td>\n",
       "      <td>27,00816474</td>\n",
       "      <td>29,51941562</td>\n",
       "      <td>...</td>\n",
       "      <td>24,43</td>\n",
       "      <td>34,83</td>\n",
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       "      <td>30.07.2022</td>\n",
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       "      <th>3</th>\n",
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       "      <td>34,61254492</td>\n",
       "      <td>32,48908844</td>\n",
       "      <td>18,0972944</td>\n",
       "      <td>11,58519829</td>\n",
       "      <td>4,974161468</td>\n",
       "      <td>10,80479077</td>\n",
       "      <td>18,3255071</td>\n",
       "      <td>26,29356837</td>\n",
       "      <td>29,38139106</td>\n",
       "      <td>...</td>\n",
       "      <td>24,43</td>\n",
       "      <td>34,83</td>\n",
       "      <td>14,46</td>\n",
       "      <td>55,31</td>\n",
       "      <td>99,99</td>\n",
       "      <td>16,83</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>22,97525157</td>\n",
       "      <td>38,06447654</td>\n",
       "      <td>26,0674464</td>\n",
       "      <td>10,0414978</td>\n",
       "      <td>6,048192956</td>\n",
       "      <td>10,84556282</td>\n",
       "      <td>17,86220086</td>\n",
       "      <td>26,51892102</td>\n",
       "      <td>28,87678772</td>\n",
       "      <td>...</td>\n",
       "      <td>24,43</td>\n",
       "      <td>34,83</td>\n",
       "      <td>14,46</td>\n",
       "      <td>55,31</td>\n",
       "      <td>99,99</td>\n",
       "      <td>16,83</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
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       "      <td>32,38603201</td>\n",
       "      <td>33,69754946</td>\n",
       "      <td>22,17075166</td>\n",
       "      <td>10,46505772</td>\n",
       "      <td>4,977706766</td>\n",
       "      <td>12,20765775</td>\n",
       "      <td>17,92326411</td>\n",
       "      <td>25,91489525</td>\n",
       "      <td>28,55151239</td>\n",
       "      <td>...</td>\n",
       "      <td>24,43</td>\n",
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       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Id     Green_MS    Yellow_MS   Orange1_MS   Orange2_MS       Red_MS  \\\n",
       "1  1  16,90465002  37,99807254   24,7728534  9,366119068  5,255775212   \n",
       "2  2  17,64092354  34,05604382  21,41426875  11,13525907  6,622319315   \n",
       "3  3  34,61254492  32,48908844   18,0972944  11,58519829  4,974161468   \n",
       "4  4  22,97525157  38,06447654   26,0674464   10,0414978  6,048192956   \n",
       "5  5  32,38603201  33,69754946  22,17075166  10,46505772  4,977706766   \n",
       "\n",
       "     Yellow_TE    Orange_TE      Cyan_TE     Dblue_TE  ... Sicaklik_Ort  \\\n",
       "1  11,38044948   17,7683399  26,38964786  29,13040372  ...        24,43   \n",
       "2  10,96859475  19,13446622  27,00816474  29,51941562  ...        24,43   \n",
       "3  10,80479077   18,3255071  26,29356837  29,38139106  ...        24,43   \n",
       "4  10,84556282  17,86220086  26,51892102  28,87678772  ...        24,43   \n",
       "5  12,20765775  17,92326411  25,91489525  28,55151239  ...        24,43   \n",
       "\n",
       "  Sicaklik_Max Sicaklik_Min Nem_Ort Nem_Max Nem_Min Yagis Ilaclama Kulleme  \\\n",
       "1        34,83        14,46   55,31   99,99   16,83     0        0       0   \n",
       "2        34,83        14,46   55,31   99,99   16,83     0        0       0   \n",
       "3        34,83        14,46   55,31   99,99   16,83     0        0       0   \n",
       "4        34,83        14,46   55,31   99,99   16,83     0        0       0   \n",
       "5        34,83        14,46   55,31   99,99   16,83     0        0       0   \n",
       "\n",
       "        Tarih  \n",
       "1  30.07.2022  \n",
       "2  30.07.2022  \n",
       "3  30.07.2022  \n",
       "4  30.07.2022  \n",
       "5  30.07.2022  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7574be10",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15945</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15946</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15947</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15947 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Id  Green_MS  Yellow_MS  Orange1_MS  Orange2_MS  Red_MS  Yellow_TE  \\\n",
       "1      False     False      False       False       False   False      False   \n",
       "2      False     False      False       False       False   False      False   \n",
       "3      False     False      False       False       False   False      False   \n",
       "4      False     False      False       False       False   False      False   \n",
       "5      False     False      False       False       False   False      False   \n",
       "...      ...       ...        ...         ...         ...     ...        ...   \n",
       "15943  False     False      False       False       False   False      False   \n",
       "15944  False     False      False       False       False   False      False   \n",
       "15945  False     False      False       False       False   False      False   \n",
       "15946  False     False      False       False       False   False      False   \n",
       "15947  False     False      False       False       False   False      False   \n",
       "\n",
       "       Orange_TE  Cyan_TE  Dblue_TE  ...  Sicaklik_Ort  Sicaklik_Max  \\\n",
       "1          False    False     False  ...         False         False   \n",
       "2          False    False     False  ...         False         False   \n",
       "3          False    False     False  ...         False         False   \n",
       "4          False    False     False  ...         False         False   \n",
       "5          False    False     False  ...         False         False   \n",
       "...          ...      ...       ...  ...           ...           ...   \n",
       "15943      False    False     False  ...         False         False   \n",
       "15944      False    False     False  ...         False         False   \n",
       "15945      False    False     False  ...         False         False   \n",
       "15946      False    False     False  ...         False         False   \n",
       "15947      False    False     False  ...         False         False   \n",
       "\n",
       "       Sicaklik_Min  Nem_Ort  Nem_Max  Nem_Min  Yagis  Ilaclama  Kulleme  \\\n",
       "1             False    False    False    False  False     False    False   \n",
       "2             False    False    False    False  False     False    False   \n",
       "3             False    False    False    False  False     False    False   \n",
       "4             False    False    False    False  False     False    False   \n",
       "5             False    False    False    False  False     False    False   \n",
       "...             ...      ...      ...      ...    ...       ...      ...   \n",
       "15943         False    False    False    False  False     False    False   \n",
       "15944         False    False    False    False  False     False    False   \n",
       "15945         False    False    False    False  False     False    False   \n",
       "15946         False    False    False    False  False     False    False   \n",
       "15947         False    False    False    False  False     False    False   \n",
       "\n",
       "       Tarih  \n",
       "1      False  \n",
       "2      False  \n",
       "3      False  \n",
       "4      False  \n",
       "5      False  \n",
       "...      ...  \n",
       "15943  False  \n",
       "15944  False  \n",
       "15945  False  \n",
       "15946  False  \n",
       "15947  False  \n",
       "\n",
       "[15947 rows x 26 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1e801254",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test.rename(columns = {0:'Id'}, inplace = True)\n",
    "\n",
    "df_test.rename(columns = {1:'Green_MS'}, inplace = True)\n",
    "df_test.rename(columns = {2:'Yellow_MS'}, inplace = True)\n",
    "df_test.rename(columns = {3:'Orange1_MS'}, inplace = True)\n",
    "df_test.rename(columns = {4:'Orange2_MS'}, inplace = True)\n",
    "df_test.rename(columns = {5:'Red_MS'}, inplace = True)\n",
    "\n",
    "df_test.rename(columns = {6:'Yellow_TE'}, inplace = True)\n",
    "df_test.rename(columns = {7:'Orange_TE'}, inplace = True)\n",
    "df_test.rename(columns = {8:'Cyan_TE'}, inplace = True)\n",
    "df_test.rename(columns = {9:'Dblue_TE'}, inplace = True)\n",
    "df_test.rename(columns = {10:'Black_TE'}, inplace = True)\n",
    "\n",
    "df_test.rename(columns = {11:'Green_RGB'}, inplace = True)\n",
    "df_test.rename(columns = {12:'Yellow_RGB'}, inplace = True)\n",
    "df_test.rename(columns = {13:'Orange1_RGB'}, inplace = True)\n",
    "df_test.rename(columns = {14:'Orange2_RGB'}, inplace = True)\n",
    "df_test.rename(columns = {15:'Red_RGB'}, inplace = True)\n",
    "\n",
    "df_test.rename(columns = {16:'Sicaklik_Ort'}, inplace = True)\n",
    "df_test.rename(columns = {17:'Sicaklik_Max'}, inplace = True)\n",
    "df_test.rename(columns = {18:'Sicaklik_Min'}, inplace = True)\n",
    "\n",
    "df_test.rename(columns = {19:'Nem_Ort'}, inplace = True)\n",
    "df_test.rename(columns = {20:'Nem_Max'}, inplace = True)\n",
    "df_test.rename(columns = {21:'Nem_Min'}, inplace = True)\n",
    "\n",
    "df_test.rename(columns = {22:'Yagis'}, inplace = True)\n",
    "\n",
    "df_test.rename(columns = {23:'Ilaclama'}, inplace = True)\n",
    "\n",
    "df_test.rename(columns = {24:'Kulleme'}, inplace = True)\n",
    "\n",
    "df_test.rename(columns = {25:'Tarih'}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b4bfec5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>Green_MS</th>\n",
       "      <th>Yellow_MS</th>\n",
       "      <th>Orange1_MS</th>\n",
       "      <th>Orange2_MS</th>\n",
       "      <th>Red_MS</th>\n",
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       "      <th>Cyan_TE</th>\n",
       "      <th>Dblue_TE</th>\n",
       "      <th>...</th>\n",
       "      <th>Sicaklik_Ort</th>\n",
       "      <th>Sicaklik_Max</th>\n",
       "      <th>Sicaklik_Min</th>\n",
       "      <th>Nem_Ort</th>\n",
       "      <th>Nem_Max</th>\n",
       "      <th>Nem_Min</th>\n",
       "      <th>Yagis</th>\n",
       "      <th>Ilaclama</th>\n",
       "      <th>Kulleme</th>\n",
       "      <th>Tarih</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>23,46523507</td>\n",
       "      <td>35,73464073</td>\n",
       "      <td>23,52778918</td>\n",
       "      <td>11,98979214</td>\n",
       "      <td>6,847172286</td>\n",
       "      <td>11,33554527</td>\n",
       "      <td>17,61431595</td>\n",
       "      <td>26,53089801</td>\n",
       "      <td>29,963993</td>\n",
       "      <td>...</td>\n",
       "      <td>24,43</td>\n",
       "      <td>34,83</td>\n",
       "      <td>14,46</td>\n",
       "      <td>55,31</td>\n",
       "      <td>99,99</td>\n",
       "      <td>16,83</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11</td>\n",
       "      <td>20,64034438</td>\n",
       "      <td>35,27551564</td>\n",
       "      <td>26,56003674</td>\n",
       "      <td>14,35893167</td>\n",
       "      <td>8,00145964</td>\n",
       "      <td>12,08620543</td>\n",
       "      <td>18,6421443</td>\n",
       "      <td>26,07946404</td>\n",
       "      <td>28,70065989</td>\n",
       "      <td>...</td>\n",
       "      <td>24,43</td>\n",
       "      <td>34,83</td>\n",
       "      <td>14,46</td>\n",
       "      <td>55,31</td>\n",
       "      <td>99,99</td>\n",
       "      <td>16,83</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12</td>\n",
       "      <td>17,59903085</td>\n",
       "      <td>34,72988712</td>\n",
       "      <td>24,83183281</td>\n",
       "      <td>12,61522605</td>\n",
       "      <td>5,204173282</td>\n",
       "      <td>12,04194323</td>\n",
       "      <td>18,65198695</td>\n",
       "      <td>26,85445519</td>\n",
       "      <td>29,36212802</td>\n",
       "      <td>...</td>\n",
       "      <td>24,43</td>\n",
       "      <td>34,83</td>\n",
       "      <td>14,46</td>\n",
       "      <td>55,31</td>\n",
       "      <td>99,99</td>\n",
       "      <td>16,83</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>35,64322621</td>\n",
       "      <td>34,6156748</td>\n",
       "      <td>20,06508499</td>\n",
       "      <td>11,57720607</td>\n",
       "      <td>4,839157387</td>\n",
       "      <td>11,00677419</td>\n",
       "      <td>18,64434078</td>\n",
       "      <td>26,15246127</td>\n",
       "      <td>28,71222451</td>\n",
       "      <td>...</td>\n",
       "      <td>24,43</td>\n",
       "      <td>34,83</td>\n",
       "      <td>14,46</td>\n",
       "      <td>55,31</td>\n",
       "      <td>99,99</td>\n",
       "      <td>16,83</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>14</td>\n",
       "      <td>33,84753728</td>\n",
       "      <td>32,2951054</td>\n",
       "      <td>27,1826696</td>\n",
       "      <td>9,130741303</td>\n",
       "      <td>7,316803773</td>\n",
       "      <td>10,77281946</td>\n",
       "      <td>18,53509979</td>\n",
       "      <td>26,72736653</td>\n",
       "      <td>29,40978343</td>\n",
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       "      <td>24,43</td>\n",
       "      <td>34,83</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id     Green_MS    Yellow_MS   Orange1_MS   Orange2_MS       Red_MS  \\\n",
       "1  10  23,46523507  35,73464073  23,52778918  11,98979214  6,847172286   \n",
       "2  11  20,64034438  35,27551564  26,56003674  14,35893167   8,00145964   \n",
       "3  12  17,59903085  34,72988712  24,83183281  12,61522605  5,204173282   \n",
       "4  13  35,64322621   34,6156748  20,06508499  11,57720607  4,839157387   \n",
       "5  14  33,84753728   32,2951054   27,1826696  9,130741303  7,316803773   \n",
       "\n",
       "     Yellow_TE    Orange_TE      Cyan_TE     Dblue_TE  ... Sicaklik_Ort  \\\n",
       "1  11,33554527  17,61431595  26,53089801    29,963993  ...        24,43   \n",
       "2  12,08620543   18,6421443  26,07946404  28,70065989  ...        24,43   \n",
       "3  12,04194323  18,65198695  26,85445519  29,36212802  ...        24,43   \n",
       "4  11,00677419  18,64434078  26,15246127  28,71222451  ...        24,43   \n",
       "5  10,77281946  18,53509979  26,72736653  29,40978343  ...        24,43   \n",
       "\n",
       "  Sicaklik_Max Sicaklik_Min Nem_Ort Nem_Max Nem_Min Yagis Ilaclama Kulleme  \\\n",
       "1        34,83        14,46   55,31   99,99   16,83     0        0       0   \n",
       "2        34,83        14,46   55,31   99,99   16,83     0        0       0   \n",
       "3        34,83        14,46   55,31   99,99   16,83     0        0       0   \n",
       "4        34,83        14,46   55,31   99,99   16,83     0        0       0   \n",
       "5        34,83        14,46   55,31   99,99   16,83     0        0       0   \n",
       "\n",
       "        Tarih  \n",
       "1  30.07.2022  \n",
       "2  30.07.2022  \n",
       "3  30.07.2022  \n",
       "4  30.07.2022  \n",
       "5  30.07.2022  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6056828d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</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",
       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>240 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Id  Green_MS  Yellow_MS  Orange1_MS  Orange2_MS  Red_MS  Yellow_TE  \\\n",
       "1    False     False      False       False       False   False      False   \n",
       "2    False     False      False       False       False   False      False   \n",
       "3    False     False      False       False       False   False      False   \n",
       "4    False     False      False       False       False   False      False   \n",
       "5    False     False      False       False       False   False      False   \n",
       "..     ...       ...        ...         ...         ...     ...        ...   \n",
       "236  False     False      False       False       False   False      False   \n",
       "237  False     False      False       False       False   False      False   \n",
       "238  False     False      False       False       False   False      False   \n",
       "239  False     False      False       False       False   False      False   \n",
       "240  False     False      False       False       False   False      False   \n",
       "\n",
       "     Orange_TE  Cyan_TE  Dblue_TE  ...  Sicaklik_Ort  Sicaklik_Max  \\\n",
       "1        False    False     False  ...         False         False   \n",
       "2        False    False     False  ...         False         False   \n",
       "3        False    False     False  ...         False         False   \n",
       "4        False    False     False  ...         False         False   \n",
       "5        False    False     False  ...         False         False   \n",
       "..         ...      ...       ...  ...           ...           ...   \n",
       "236      False    False     False  ...         False         False   \n",
       "237      False    False     False  ...         False         False   \n",
       "238      False    False     False  ...         False         False   \n",
       "239      False    False     False  ...         False         False   \n",
       "240      False    False     False  ...         False         False   \n",
       "\n",
       "     Sicaklik_Min  Nem_Ort  Nem_Max  Nem_Min  Yagis  Ilaclama  Kulleme  Tarih  \n",
       "1           False    False    False    False  False     False    False  False  \n",
       "2           False    False    False    False  False     False    False  False  \n",
       "3           False    False    False    False  False     False    False  False  \n",
       "4           False    False    False    False  False     False    False  False  \n",
       "5           False    False    False    False  False     False    False  False  \n",
       "..            ...      ...      ...      ...    ...       ...      ...    ...  \n",
       "236         False    False    False    False  False     False    False  False  \n",
       "237         False    False    False    False  False     False    False  False  \n",
       "238         False    False    False    False  False     False    False  False  \n",
       "239         False    False    False    False  False     False    False  False  \n",
       "240         False    False    False    False  False     False    False  False  \n",
       "\n",
       "[240 rows x 26 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ce36bbe2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train[\"Green_MS\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Green_MS\"]]\n",
    "df_train[\"Yellow_MS\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Yellow_MS\"]]\n",
    "df_train[\"Orange1_MS\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Orange1_MS\"]]\n",
    "df_train[\"Orange2_MS\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Orange2_MS\"]]\n",
    "df_train[\"Red_MS\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Red_MS\"]]\n",
    "\n",
    "df_train[\"Yellow_TE\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Yellow_TE\"]]\n",
    "df_train[\"Orange_TE\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Orange_TE\"]]\n",
    "df_train[\"Cyan_TE\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Cyan_TE\"]]\n",
    "df_train[\"Dblue_TE\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Dblue_TE\"]]\n",
    "df_train[\"Black_TE\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Black_TE\"]]\n",
    "\n",
    "df_train[\"Green_RGB\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Green_RGB\"]]\n",
    "df_train[\"Yellow_RGB\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Yellow_RGB\"]]\n",
    "df_train[\"Orange1_RGB\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Orange1_RGB\"]]\n",
    "df_train[\"Orange2_RGB\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Orange2_RGB\"]]\n",
    "df_train[\"Red_RGB\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Red_RGB\"]]\n",
    "\n",
    "df_train[\"Sicaklik_Ort\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Sicaklik_Ort\"]]\n",
    "df_train[\"Sicaklik_Max\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Sicaklik_Max\"]]\n",
    "df_train[\"Sicaklik_Min\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Sicaklik_Min\"]]\n",
    "\n",
    "df_train[\"Nem_Ort\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Nem_Ort\"]]\n",
    "df_train[\"Nem_Max\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Nem_Max\"]]\n",
    "df_train[\"Nem_Min\"] = [float(str(i).replace(\",\", \".\")) for i in df_train[\"Nem_Min\"]]\n",
    "\n",
    "df_train[\"Yagis\"] = [float(str(i)) for i in df_train[\"Yagis\"]]\n",
    "\n",
    "df_train[\"Ilaclama\"] = [int(str(i)) for i in df_train[\"Ilaclama\"]]\n",
    "\n",
    "df_train[\"Kulleme\"] = [int(str(i).replace(\",\", \".\")) for i in df_train[\"Kulleme\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3bcf882c",
   "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>Id</th>\n",
       "      <th>Green_MS</th>\n",
       "      <th>Yellow_MS</th>\n",
       "      <th>Orange1_MS</th>\n",
       "      <th>Orange2_MS</th>\n",
       "      <th>Red_MS</th>\n",
       "      <th>Yellow_TE</th>\n",
       "      <th>Orange_TE</th>\n",
       "      <th>Cyan_TE</th>\n",
       "      <th>Dblue_TE</th>\n",
       "      <th>...</th>\n",
       "      <th>Sicaklik_Ort</th>\n",
       "      <th>Sicaklik_Max</th>\n",
       "      <th>Sicaklik_Min</th>\n",
       "      <th>Nem_Ort</th>\n",
       "      <th>Nem_Max</th>\n",
       "      <th>Nem_Min</th>\n",
       "      <th>Yagis</th>\n",
       "      <th>Ilaclama</th>\n",
       "      <th>Kulleme</th>\n",
       "      <th>Tarih</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>16.904650</td>\n",
       "      <td>37.998073</td>\n",
       "      <td>24.772853</td>\n",
       "      <td>9.366119</td>\n",
       "      <td>5.255775</td>\n",
       "      <td>11.380449</td>\n",
       "      <td>17.768340</td>\n",
       "      <td>26.389648</td>\n",
       "      <td>29.130404</td>\n",
       "      <td>...</td>\n",
       "      <td>24.43</td>\n",
       "      <td>34.83</td>\n",
       "      <td>14.46</td>\n",
       "      <td>55.31</td>\n",
       "      <td>99.99</td>\n",
       "      <td>16.83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>17.640924</td>\n",
       "      <td>34.056044</td>\n",
       "      <td>21.414269</td>\n",
       "      <td>11.135259</td>\n",
       "      <td>6.622319</td>\n",
       "      <td>10.968595</td>\n",
       "      <td>19.134466</td>\n",
       "      <td>27.008165</td>\n",
       "      <td>29.519416</td>\n",
       "      <td>...</td>\n",
       "      <td>24.43</td>\n",
       "      <td>34.83</td>\n",
       "      <td>14.46</td>\n",
       "      <td>55.31</td>\n",
       "      <td>99.99</td>\n",
       "      <td>16.83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>34.612545</td>\n",
       "      <td>32.489088</td>\n",
       "      <td>18.097294</td>\n",
       "      <td>11.585198</td>\n",
       "      <td>4.974161</td>\n",
       "      <td>10.804791</td>\n",
       "      <td>18.325507</td>\n",
       "      <td>26.293568</td>\n",
       "      <td>29.381391</td>\n",
       "      <td>...</td>\n",
       "      <td>24.43</td>\n",
       "      <td>34.83</td>\n",
       "      <td>14.46</td>\n",
       "      <td>55.31</td>\n",
       "      <td>99.99</td>\n",
       "      <td>16.83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>22.975252</td>\n",
       "      <td>38.064477</td>\n",
       "      <td>26.067446</td>\n",
       "      <td>10.041498</td>\n",
       "      <td>6.048193</td>\n",
       "      <td>10.845563</td>\n",
       "      <td>17.862201</td>\n",
       "      <td>26.518921</td>\n",
       "      <td>28.876788</td>\n",
       "      <td>...</td>\n",
       "      <td>24.43</td>\n",
       "      <td>34.83</td>\n",
       "      <td>14.46</td>\n",
       "      <td>55.31</td>\n",
       "      <td>99.99</td>\n",
       "      <td>16.83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>32.386032</td>\n",
       "      <td>33.697549</td>\n",
       "      <td>22.170752</td>\n",
       "      <td>10.465058</td>\n",
       "      <td>4.977707</td>\n",
       "      <td>12.207658</td>\n",
       "      <td>17.923264</td>\n",
       "      <td>25.914895</td>\n",
       "      <td>28.551512</td>\n",
       "      <td>...</td>\n",
       "      <td>24.43</td>\n",
       "      <td>34.83</td>\n",
       "      <td>14.46</td>\n",
       "      <td>55.31</td>\n",
       "      <td>99.99</td>\n",
       "      <td>16.83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.07.2022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Id   Green_MS  Yellow_MS  Orange1_MS  Orange2_MS    Red_MS  Yellow_TE  \\\n",
       "1  1  16.904650  37.998073   24.772853    9.366119  5.255775  11.380449   \n",
       "2  2  17.640924  34.056044   21.414269   11.135259  6.622319  10.968595   \n",
       "3  3  34.612545  32.489088   18.097294   11.585198  4.974161  10.804791   \n",
       "4  4  22.975252  38.064477   26.067446   10.041498  6.048193  10.845563   \n",
       "5  5  32.386032  33.697549   22.170752   10.465058  4.977707  12.207658   \n",
       "\n",
       "   Orange_TE    Cyan_TE   Dblue_TE  ...  Sicaklik_Ort  Sicaklik_Max  \\\n",
       "1  17.768340  26.389648  29.130404  ...         24.43         34.83   \n",
       "2  19.134466  27.008165  29.519416  ...         24.43         34.83   \n",
       "3  18.325507  26.293568  29.381391  ...         24.43         34.83   \n",
       "4  17.862201  26.518921  28.876788  ...         24.43         34.83   \n",
       "5  17.923264  25.914895  28.551512  ...         24.43         34.83   \n",
       "\n",
       "   Sicaklik_Min  Nem_Ort  Nem_Max  Nem_Min  Yagis  Ilaclama  Kulleme  \\\n",
       "1         14.46    55.31    99.99    16.83    0.0         0        0   \n",
       "2         14.46    55.31    99.99    16.83    0.0         0        0   \n",
       "3         14.46    55.31    99.99    16.83    0.0         0        0   \n",
       "4         14.46    55.31    99.99    16.83    0.0         0        0   \n",
       "5         14.46    55.31    99.99    16.83    0.0         0        0   \n",
       "\n",
       "        Tarih  \n",
       "1  30.07.2022  \n",
       "2  30.07.2022  \n",
       "3  30.07.2022  \n",
       "4  30.07.2022  \n",
       "5  30.07.2022  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ffdb4ed6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test[\"Green_MS\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Green_MS\"]]\n",
    "df_test[\"Yellow_MS\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Yellow_MS\"]]\n",
    "df_test[\"Orange1_MS\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Orange1_MS\"]]\n",
    "df_test[\"Orange2_MS\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Orange2_MS\"]]\n",
    "df_test[\"Red_MS\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Red_MS\"]]\n",
    "\n",
    "df_test[\"Yellow_TE\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Yellow_TE\"]]\n",
    "df_test[\"Orange_TE\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Orange_TE\"]]\n",
    "df_test[\"Cyan_TE\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Cyan_TE\"]]\n",
    "df_test[\"Dblue_TE\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Dblue_TE\"]]\n",
    "df_test[\"Black_TE\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Black_TE\"]]\n",
    "\n",
    "df_test[\"Green_RGB\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Green_RGB\"]]\n",
    "df_test[\"Yellow_RGB\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Yellow_RGB\"]]\n",
    "df_test[\"Orange1_RGB\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Orange1_RGB\"]]\n",
    "df_test[\"Orange2_RGB\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Orange2_RGB\"]]\n",
    "df_test[\"Red_RGB\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Red_RGB\"]]\n",
    "\n",
    "df_test[\"Sicaklik_Ort\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Sicaklik_Ort\"]]\n",
    "df_test[\"Sicaklik_Max\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Sicaklik_Max\"]]\n",
    "df_test[\"Sicaklik_Min\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Sicaklik_Min\"]]\n",
    "\n",
    "df_test[\"Sicaklik_Ort\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Sicaklik_Ort\"]]\n",
    "df_test[\"Sicaklik_Max\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Sicaklik_Max\"]]\n",
    "df_test[\"Sicaklik_Min\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Sicaklik_Min\"]]\n",
    "\n",
    "df_test[\"Nem_Ort\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Nem_Ort\"]]\n",
    "df_test[\"Nem_Max\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Nem_Max\"]]\n",
    "df_test[\"Nem_Min\"] = [float(str(i).replace(\",\", \".\")) for i in df_test[\"Nem_Min\"]]\n",
    "\n",
    "df_test[\"Yagis\"] = [float(str(i)) for i in df_test[\"Yagis\"]]\n",
    "\n",
    "df_test[\"Ilaclama\"] = [int(str(i)) for i in df_test[\"Ilaclama\"]]\n",
    "\n",
    "df_test[\"Kulleme\"] = [int(str(i).replace(\",\", \".\")) for i in df_test[\"Kulleme\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b7d801af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = df_train[[\"Green_MS\",\"Yellow_MS\",\"Orange1_MS\",\"Orange2_MS\",\"Red_MS\",'Yellow_TE','Orange_TE','Cyan_TE','Dblue_TE','Black_TE','Green_RGB','Yellow_RGB','Orange1_RGB','Orange2_RGB','Red_RGB','Sicaklik_Ort',\"Sicaklik_Max\",\"Sicaklik_Min\",\"Nem_Ort\",\"Nem_Max\",'Nem_Min','Ilaclama']]\n",
    "y = df_train['Kulleme']\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(15,10))\n",
    "\n",
    "sns.heatmap(X.corr(), annot = True, ax=ax)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "758ddefd",
   "metadata": {},
   "source": [
    "#Setting the value for X and Y\n",
    "X_train = df_train[[\"Green_MS\",\"Yellow_MS\",\"Orange1_MS\",\"Orange2_MS\",\"Red_MS\",'Yellow_TE','Orange_TE','Cyan_TE','Dblue_TE','Black_TE','Green_RGB','Yellow_RGB','Orange1_RGB','Orange2_RGB','Red_RGB','Sicaklik_Ort',\"Sicaklik_Max\",\"Sicaklik_Min\",\"Nem_Ort\",\"Nem_Max\",'Nem_Min',\"Yagis\",'Yaprak_Islaklik','Ilaclama']].values\n",
    "y_train = df_train['Cercospora'].values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcc08834",
   "metadata": {},
   "source": [
    "#Setting the value for X and Y\n",
    "X_test = df_test[[\"Green_MS\",\"Yellow_MS\",\"Orange1_MS\",\"Orange2_MS\",\"Red_MS\",'Yellow_TE','Orange_TE','Cyan_TE','Dblue_TE','Black_TE','Green_RGB','Yellow_RGB','Orange1_RGB','Orange2_RGB','Red_RGB','Sicaklik_Ort',\"Sicaklik_Max\",\"Sicaklik_Min\",\"Nem_Ort\",\"Nem_Max\",'Nem_Min',\"Yagis\",'Yaprak_Islaklik','Ilaclama']].values\n",
    "y_test = df_test['Cercospora'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "c77747d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Setting the value for X and Y \n",
    "X_train = df_train[['Orange1_RGB','Red_RGB',\"Sicaklik_Min\",\"Nem_Ort\",'Ilaclama']].values \n",
    "y_train = df_train['Kulleme'].values\n",
    "\n",
    "#Setting the value for X and Y \n",
    "X_test = df_test[['Orange1_RGB','Red_RGB',\"Sicaklik_Min\",\"Nem_Ort\",'Ilaclama']].values \n",
    "y_test = df_test['Kulleme'].values\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d512a13",
   "metadata": {},
   "source": [
    "\n",
    "#Setting the value for X and Y\n",
    "X_train = df_train[['Yellow_TE','Orange_TE','Cyan_TE','Dblue_TE','Black_TE']].values\n",
    "y_train = df_train['Cercospora'].values\n",
    "\n",
    "#Setting the value for X and Y\n",
    "X_test = df_test[['Yellow_TE','Orange_TE','Cyan_TE','Dblue_TE','Black_TE']].values\n",
    "y_test = df_test['Cercospora'].values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d18b988",
   "metadata": {},
   "source": [
    "\n",
    "#Setting the value for X and Y\n",
    "X_train = df_train[['Green_RGB','Yellow_RGB','Orange1_RGB','Orange2_RGB','Red_RGB']].values\n",
    "y_train = df_train['Cercospora'].values\n",
    "\n",
    "#Setting the value for X and Y\n",
    "X_test = df_test[['Green_RGB','Yellow_RGB','Orange1_RGB','Orange2_RGB','Red_RGB']].values\n",
    "y_test = df_test['Cercospora'].values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74665c13",
   "metadata": {},
   "source": [
    "#Setting the value for X and Y\n",
    "X_train = df_train[[\"Green_MS\",\"Yellow_MS\",\"Orange1_MS\",\"Orange2_MS\",\"Red_MS\",'Sicaklik_Ort']].values\n",
    "y_train = df_train['Cercospora'].values\n",
    "\n",
    "#Setting the value for X and Y\n",
    "X_test = df_test[[\"Green_MS\",\"Yellow_MS\",\"Orange1_MS\",\"Orange2_MS\",\"Red_MS\",'Sicaklik_Ort']].values\n",
    "y_test = df_test['Cercospora'].values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cda07704",
   "metadata": {},
   "source": [
    "#Setting the value for X and Y \n",
    "X_train = df_train[['Yellow_TE','Orange_TE','Cyan_TE','Dblue_TE','Black_TE','Sicaklik_Ort',\"Yagis\",'Yaprak_Islaklik']].values \n",
    "y_train = df_train['Cercospora'].values\n",
    "\n",
    "#Setting the value for X and Y \n",
    "X_test = df_test[['Yellow_TE','Orange_TE','Cyan_TE','Dblue_TE','Black_TE','Sicaklik_Ort',\"Yagis\",'Yaprak_Islaklik']].values \n",
    "y_test = df_test['Cercospora'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "2461072d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "# https://www.veribilimiokulu.com/naive-bayes-yontemiyle-siniflandirma-classification-with-naive-bayes-python-ile-uygulama/\n",
    "\n",
    "sc_X = StandardScaler()\n",
    "X_train = sc_X.fit_transform(X_train)\n",
    "X_test = sc_X.transform(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3586527",
   "metadata": {},
   "source": [
    "### Logistic Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "7e83ce34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "reg_model = LinearRegression()  \n",
    "reg_model.fit(X_train, y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "aa1ad753",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prediction for test set: [ 0.37483021  0.38635274  0.37784261  0.37173867  0.3698272   0.38028907\n",
      "  0.39467921  0.37710971  0.37907597  0.38641837  0.38920379  0.36802647\n",
      "  0.37260094  0.39183214  0.37736419  0.36119805  0.37152561  0.36280331\n",
      "  0.38123305  0.37580618  0.37039081  0.37742928  0.37596438  0.36497416\n",
      "  0.36369134  0.37079005  0.37892574  0.37680454  0.3733779   0.36878977\n",
      "  0.41030547  0.4411221   0.38668003  0.38462306  0.37789179  0.39119597\n",
      "  0.9509265   0.92763036  0.92863521  0.96115845  0.92973283  0.92132335\n",
      "  0.98867901  0.94653175  0.94274204  0.97313213  0.93941572  0.95944892\n",
      "  0.92462689  0.92858025  0.97593006  0.97381485  0.98889157  0.91626039\n",
      "  0.93084809  0.96808303  0.94494532  0.96836365  0.92553539  0.96114903\n",
      "  0.9493346   0.94552279  0.92958849  0.93059343  0.98222727  0.9663973\n",
      "  0.35364522  0.35039685  0.36127468  0.36100176  0.35290062  0.35246976\n",
      "  0.34798599  0.35847721  0.34456684  0.3600369   0.35054766  0.35373046\n",
      "  0.34937933  0.36705651  0.36651077  0.36554607  0.35506674  1.25840921\n",
      "  1.26005754  1.26594879  1.25494309  1.26442069  1.25395635  1.25676681\n",
      "  1.25578764  1.20839743  1.20059427  1.22239965  1.1997757   1.20147077\n",
      "  0.37997363  0.37189856  0.36705254  0.36011413  0.38368183  0.40173877\n",
      "  0.41187424  0.37865186  0.37825135  0.39285515  0.43808802  0.39493211\n",
      "  0.38431227  0.38541024  0.38414192  0.44348341  0.40258736  0.37265551\n",
      "  0.38349812  0.35977325  0.38433093  0.37339704  0.38721682  0.36751855\n",
      "  0.13957004  0.13466971  0.14491876  0.14818537  0.12946872  0.12964234\n",
      "  0.12131706  0.11626637  0.11817389  0.12387233  0.13525948  0.11868737\n",
      "  0.14475394  0.13789225  0.07616614  0.12236492  0.08984026  0.09293659\n",
      "  0.07417165  0.11412691  0.09394347  0.06133851  0.08141336  0.04458608\n",
      "  0.06649821  0.07677511  0.12077043  0.11454932  0.03685522  0.01223958\n",
      "  0.03817541  0.00850906  0.03271949  0.00135478  0.01927431 -0.0022954\n",
      "  0.031953    0.03556902  0.01996605  0.01738276  0.03815475  0.98264805\n",
      "  0.96741292  0.98928943  0.93342377  1.00749645  0.9244245   0.92549371\n",
      "  0.9511167   0.98765294  0.98142053  0.93638824  0.9630712   0.97396014\n",
      "  0.97710106  0.96100337  0.95079901  0.96714353  0.9903183   0.99656651\n",
      "  0.94593591  0.98438358  0.98449385  0.95156136  0.97470417  1.00181514\n",
      "  0.98673518  1.00458616  0.97528815  0.97590693  0.90528854  0.85347453\n",
      "  0.8569091   0.84484932  0.87857054  0.91505305  0.86885221  0.85308878\n",
      "  0.84038581  0.90720238  0.90470139  0.85203069  0.88219661  0.87549354\n",
      "  0.84842758  0.89545231  0.85215328  0.88303063  0.88500287  0.8733707\n",
      "  0.86906342  0.86140502  0.86296353  0.87570158  0.87106401  0.87936943\n",
      "  0.87446716  0.86672953  0.87117698  0.87854981  0.85933805  0.87039677\n",
      "  0.86976532  0.86710345  0.84423611  0.8843854   0.87637176  0.84352334\n",
      "  0.8505238   0.86671963  0.8764108   0.86808197  0.87027946  0.86416704\n",
      "  0.86539185  0.86596302  0.85054599  0.86486701  0.92009133  0.92743693]\n"
     ]
    }
   ],
   "source": [
    "y_pred_reg= reg_model.predict(X_test)\n",
    "\n",
    "print(\"Prediction for test set: {}\".format(y_pred_reg))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "25ab283a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9291666666666667\n",
      "0.20488781697606256\n",
      "0.07474250100729098\n",
      "0.27339074784507794\n"
     ]
    }
   ],
   "source": [
    "# calculate MAE, MSE, RMSE\n",
    "import sklearn.metrics as metrics\n",
    "print(\"Accuracy:\",metrics.accuracy_score(y_test, y_pred_reg.round()))\n",
    "\n",
    "print(metrics.mean_absolute_error(y_test, y_pred_reg))\n",
    "print(metrics.mean_squared_error(y_test, y_pred_reg))\n",
    "print(np.sqrt(metrics.mean_squared_error(y_test, y_pred_reg)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "24631827",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[101   0]\n",
      " [ 17 122]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "print(confusion_matrix(y_test, y_pred_reg.round()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f396d2e9",
   "metadata": {},
   "source": [
    "### KNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "4a61649b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "knn_model = KNeighborsRegressor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "bc299fa0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsRegressor()"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn_model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "e708dad6",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prediction for test set: [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n",
      " 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n",
      " 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n",
      " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.\n",
      " 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n",
      " 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n",
      " 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]\n"
     ]
    }
   ],
   "source": [
    "y_pred_knn= knn_model.predict(X_test)\n",
    "\n",
    "print(\"Prediction for test set: {}\".format(y_pred_knn))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "e6e0884e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 1.0\n",
      "0.0\n",
      "0.0\n",
      "0.0\n"
     ]
    }
   ],
   "source": [
    "import sklearn.metrics as metrics\n",
    "print(\"Accuracy:\",metrics.accuracy_score(y_test,  y_pred_knn.round()))\n",
    "\n",
    "print(metrics.mean_absolute_error(y_test, y_pred_knn))\n",
    "print(metrics.mean_squared_error(y_test, y_pred_knn))\n",
    "print(np.sqrt(metrics.mean_squared_error(y_test, y_pred_knn)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "35fe969c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[101   0]\n",
      " [  0 139]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "print(confusion_matrix(y_test, y_pred_knn.round()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f66c88d8",
   "metadata": {},
   "source": [
    "### Decision Tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "5abb3a4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.tree import export_text\n",
    "\n",
    "decision_tree_model = DecisionTreeClassifier(random_state=0, max_depth=5)\n",
    "\n",
    "decision_tree_model = decision_tree_model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "d5e728c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prediction for test set: [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]\n"
     ]
    }
   ],
   "source": [
    "y_pred_tree= decision_tree_model.predict(X_test)\n",
    "\n",
    "print(\"Prediction for test set: {}\".format(y_pred_tree))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "e22c3a4d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 1.0\n",
      "0.0\n",
      "0.0\n",
      "0.0\n"
     ]
    }
   ],
   "source": [
    "import sklearn.metrics as metrics\n",
    "print(\"Accuracy:\",metrics.accuracy_score(y_test, y_pred_tree))\n",
    "\n",
    "print(metrics.mean_absolute_error(y_test, y_pred_tree))\n",
    "print(metrics.mean_squared_error(y_test, y_pred_tree))\n",
    "print(np.sqrt(metrics.mean_squared_error(y_test, y_pred_tree)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "15e93630",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[101   0]\n",
      " [  0 139]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "print(confusion_matrix(y_test, y_pred_tree))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a230009",
   "metadata": {},
   "source": [
    "### SVM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "1c95677c",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import svm\n",
    "svm_model = svm.SVC()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "534d1996",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC()"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "svm_model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "2b6a1344",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prediction for test set: [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]\n"
     ]
    }
   ],
   "source": [
    "y_pred_svm= svm_model.predict(X_test)\n",
    "\n",
    "print(\"Prediction for test set: {}\".format(y_pred_svm))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "0146b338",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 1.0\n",
      "0.0\n",
      "0.0\n",
      "0.0\n"
     ]
    }
   ],
   "source": [
    "import sklearn.metrics as metrics\n",
    "print(\"Accuracy:\",metrics.accuracy_score(y_test, y_pred_svm))\n",
    "\n",
    "print(metrics.mean_absolute_error(y_test, y_pred_svm))\n",
    "print(metrics.mean_squared_error(y_test, y_pred_svm))\n",
    "print(np.sqrt(metrics.mean_squared_error(y_test, y_pred_svm)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "8db2ae78",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[101   0]\n",
      " [  0 139]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "print(confusion_matrix(y_test, y_pred_svm))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42362ae9",
   "metadata": {},
   "source": [
    "### Gaussian"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "5fbf7a35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GaussianNB()"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.naive_bayes import GaussianNB\n",
    "\n",
    "gaus_model = GaussianNB()\n",
    "\n",
    "gaus_model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "0adc5544",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prediction for test set: [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]\n"
     ]
    }
   ],
   "source": [
    "y_pred_gauss = gaus_model.predict(X_test)\n",
    "\n",
    "print(\"Prediction for test set: {}\".format(y_pred_gauss))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "39eadcfc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9291666666666667\n",
      "0.07083333333333333\n",
      "0.07083333333333333\n",
      "0.26614532371118854\n"
     ]
    }
   ],
   "source": [
    "import sklearn.metrics as metrics\n",
    "print(\"Accuracy:\",metrics.accuracy_score(y_test, y_pred_gauss))\n",
    "\n",
    "print(metrics.mean_absolute_error(y_test, y_pred_gauss))\n",
    "print(metrics.mean_squared_error(y_test, y_pred_gauss))\n",
    "print(np.sqrt(metrics.mean_squared_error(y_test, y_pred_gauss)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "1f94dc13",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[101   0]\n",
      " [ 17 122]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "print(confusion_matrix(y_test, y_pred_gauss))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "45e336ec",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a3ba4eab",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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