Finding_Exoplanets.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import math\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "import numpy as np \n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('fivethirtyeight')\n",
    "from pylab import rcParams\n",
    "rcParams['figure.figsize'] = 10 , 6\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error\n",
    "from imblearn.over_sampling import SMOTE\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import linear_model\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.metrics import precision_score, recall_score, roc_curve, f1_score, roc_auc_score,confusion_matrix, accuracy_score, classification_report\n",
    "from sklearn.preprocessing import StandardScaler, normalize\n",
    "from scipy import ndimage\n",
    "import seaborn as sns\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_data = pd.read_csv('D:/The_ultimate_coding/Exoplanet_prediction/exoTest.csv').fillna(0)\n",
    "train_data = pd.read_csv('D:/The_ultimate_coding/Exoplanet_prediction/exoTrain.csv').fillna(0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        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>LABEL</th>\n",
       "      <th>FLUX.1</th>\n",
       "      <th>FLUX.2</th>\n",
       "      <th>FLUX.3</th>\n",
       "      <th>FLUX.4</th>\n",
       "      <th>FLUX.5</th>\n",
       "      <th>FLUX.6</th>\n",
       "      <th>FLUX.7</th>\n",
       "      <th>FLUX.8</th>\n",
       "      <th>FLUX.9</th>\n",
       "      <th>...</th>\n",
       "      <th>FLUX.3188</th>\n",
       "      <th>FLUX.3189</th>\n",
       "      <th>FLUX.3190</th>\n",
       "      <th>FLUX.3191</th>\n",
       "      <th>FLUX.3192</th>\n",
       "      <th>FLUX.3193</th>\n",
       "      <th>FLUX.3194</th>\n",
       "      <th>FLUX.3195</th>\n",
       "      <th>FLUX.3196</th>\n",
       "      <th>FLUX.3197</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>93.85</td>\n",
       "      <td>83.81</td>\n",
       "      <td>20.10</td>\n",
       "      <td>-26.98</td>\n",
       "      <td>-39.56</td>\n",
       "      <td>-124.71</td>\n",
       "      <td>-135.18</td>\n",
       "      <td>-96.27</td>\n",
       "      <td>-79.89</td>\n",
       "      <td>...</td>\n",
       "      <td>-78.07</td>\n",
       "      <td>-102.15</td>\n",
       "      <td>-102.15</td>\n",
       "      <td>25.13</td>\n",
       "      <td>48.57</td>\n",
       "      <td>92.54</td>\n",
       "      <td>39.32</td>\n",
       "      <td>61.42</td>\n",
       "      <td>5.08</td>\n",
       "      <td>-39.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>-38.88</td>\n",
       "      <td>-33.83</td>\n",
       "      <td>-58.54</td>\n",
       "      <td>-40.09</td>\n",
       "      <td>-79.31</td>\n",
       "      <td>-72.81</td>\n",
       "      <td>-86.55</td>\n",
       "      <td>-85.33</td>\n",
       "      <td>-83.97</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.28</td>\n",
       "      <td>-32.21</td>\n",
       "      <td>-32.21</td>\n",
       "      <td>-24.89</td>\n",
       "      <td>-4.86</td>\n",
       "      <td>0.76</td>\n",
       "      <td>-11.70</td>\n",
       "      <td>6.46</td>\n",
       "      <td>16.00</td>\n",
       "      <td>19.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>532.64</td>\n",
       "      <td>535.92</td>\n",
       "      <td>513.73</td>\n",
       "      <td>496.92</td>\n",
       "      <td>456.45</td>\n",
       "      <td>466.00</td>\n",
       "      <td>464.50</td>\n",
       "      <td>486.39</td>\n",
       "      <td>436.56</td>\n",
       "      <td>...</td>\n",
       "      <td>-71.69</td>\n",
       "      <td>13.31</td>\n",
       "      <td>13.31</td>\n",
       "      <td>-29.89</td>\n",
       "      <td>-20.88</td>\n",
       "      <td>5.06</td>\n",
       "      <td>-11.80</td>\n",
       "      <td>-28.91</td>\n",
       "      <td>-70.02</td>\n",
       "      <td>-96.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>326.52</td>\n",
       "      <td>347.39</td>\n",
       "      <td>302.35</td>\n",
       "      <td>298.13</td>\n",
       "      <td>317.74</td>\n",
       "      <td>312.70</td>\n",
       "      <td>322.33</td>\n",
       "      <td>311.31</td>\n",
       "      <td>312.42</td>\n",
       "      <td>...</td>\n",
       "      <td>5.71</td>\n",
       "      <td>-3.73</td>\n",
       "      <td>-3.73</td>\n",
       "      <td>30.05</td>\n",
       "      <td>20.03</td>\n",
       "      <td>-12.67</td>\n",
       "      <td>-8.77</td>\n",
       "      <td>-17.31</td>\n",
       "      <td>-17.35</td>\n",
       "      <td>13.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>-1107.21</td>\n",
       "      <td>-1112.59</td>\n",
       "      <td>-1118.95</td>\n",
       "      <td>-1095.10</td>\n",
       "      <td>-1057.55</td>\n",
       "      <td>-1034.48</td>\n",
       "      <td>-998.34</td>\n",
       "      <td>-1022.71</td>\n",
       "      <td>-989.57</td>\n",
       "      <td>...</td>\n",
       "      <td>-594.37</td>\n",
       "      <td>-401.66</td>\n",
       "      <td>-401.66</td>\n",
       "      <td>-357.24</td>\n",
       "      <td>-443.76</td>\n",
       "      <td>-438.54</td>\n",
       "      <td>-399.71</td>\n",
       "      <td>-384.65</td>\n",
       "      <td>-411.79</td>\n",
       "      <td>-510.54</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 3198 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   LABEL   FLUX.1   FLUX.2   FLUX.3   FLUX.4   FLUX.5   FLUX.6  FLUX.7  \\\n",
       "0      2    93.85    83.81    20.10   -26.98   -39.56  -124.71 -135.18   \n",
       "1      2   -38.88   -33.83   -58.54   -40.09   -79.31   -72.81  -86.55   \n",
       "2      2   532.64   535.92   513.73   496.92   456.45   466.00  464.50   \n",
       "3      2   326.52   347.39   302.35   298.13   317.74   312.70  322.33   \n",
       "4      2 -1107.21 -1112.59 -1118.95 -1095.10 -1057.55 -1034.48 -998.34   \n",
       "\n",
       "    FLUX.8  FLUX.9  ...  FLUX.3188  FLUX.3189  FLUX.3190  FLUX.3191  \\\n",
       "0   -96.27  -79.89  ...     -78.07    -102.15    -102.15      25.13   \n",
       "1   -85.33  -83.97  ...      -3.28     -32.21     -32.21     -24.89   \n",
       "2   486.39  436.56  ...     -71.69      13.31      13.31     -29.89   \n",
       "3   311.31  312.42  ...       5.71      -3.73      -3.73      30.05   \n",
       "4 -1022.71 -989.57  ...    -594.37    -401.66    -401.66    -357.24   \n",
       "\n",
       "   FLUX.3192  FLUX.3193  FLUX.3194  FLUX.3195  FLUX.3196  FLUX.3197  \n",
       "0      48.57      92.54      39.32      61.42       5.08     -39.54  \n",
       "1      -4.86       0.76     -11.70       6.46      16.00      19.93  \n",
       "2     -20.88       5.06     -11.80     -28.91     -70.02     -96.67  \n",
       "3      20.03     -12.67      -8.77     -17.31     -17.35      13.98  \n",
       "4    -443.76    -438.54    -399.71    -384.65    -411.79    -510.54  \n",
       "\n",
       "[5 rows x 3198 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "categ = {2: 1,1: 0}\n",
    "train_data.LABEL = [categ[item] for item in train_data.LABEL]\n",
    "test_data.LABEL = [categ[item] for item in test_data.LABEL]\n",
    "#now the target column label consist of two categories one doesnt consist of exoplanets and one consist of exoplanets\n",
    "#so converting  them to binary values for easier processing of data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Reduce memory\n",
    "def reduce_memory(df):\n",
    "    \"\"\" iterate through all the columns of a dataframe and modify the data type\n",
    "        to reduce memory usage.        \n",
    "    \"\"\"\n",
    "    start_mem = df.memory_usage().sum() / 1024**2\n",
    "    print('Memory usage of dataframe is {:.2f} MB'.format(start_mem))\n",
    "    \n",
    "    for col in df.columns:\n",
    "        col_type = df[col].dtype\n",
    "        \n",
    "        if col_type != object:\n",
    "            c_min = df[col].min()\n",
    "            c_max = df[col].max()\n",
    "            if str(col_type)[:3] == 'int':\n",
    "                if c_min > np.iinfo(np.int8).min and c_max < np.iinfo(np.int8).max:\n",
    "                    df[col] = df[col].astype(np.int8)\n",
    "                elif c_min > np.iinfo(np.int16).min and c_max < np.iinfo(np.int16).max:\n",
    "                    df[col] = df[col].astype(np.int16)\n",
    "                elif c_min > np.iinfo(np.int32).min and c_max < np.iinfo(np.int32).max:\n",
    "                    df[col] = df[col].astype(np.int32)\n",
    "                elif c_min > np.iinfo(np.int64).min and c_max < np.iinfo(np.int64).max:\n",
    "                    df[col] = df[col].astype(np.int64)  \n",
    "            else:\n",
    "                if c_min > np.finfo(np.float16).min and c_max < np.finfo(np.float16).max:\n",
    "                    df[col] = df[col].astype(np.float16)\n",
    "                elif c_min > np.finfo(np.float32).min and c_max < np.finfo(np.float32).max:\n",
    "                    df[col] = df[col].astype(np.float32)\n",
    "                else:\n",
    "                    df[col] = df[col].astype(np.float64)\n",
    "        else:\n",
    "            df[col] = df[col].astype('category').end_mem = df.memory_usage().sum() / 1024**2\n",
    "    print('Memory usage after optimization is: {:.2f} MB'.format(end_mem))\n",
    "    print('Decreased by {:.1f}%'.format(100 * (start_mem - end_mem) / start_mem))\n",
    "    return test_data, reduce_memory(test_data)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Class Distribution \\n (0: NotExoplanet  || 1: Exoplanet)')"
      ]
     },
     "execution_count": 17,
     "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.figure(figsize=(6,4))\n",
    "colors = [\"0\", \"1\"]\n",
    "sns.countplot('LABEL', data=train_data, palette=colors)\n",
    "plt.title('Class Distribution \\n (0: NotExoplanet  || 1: Exoplanet)', fontsize=14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pylab import rcParams\n",
    "rcParams['figure.figsize'] = 13, 8\n",
    "plt.title('Distribution of flux values', fontsize=10)\n",
    "plt.xlabel('Flux values')\n",
    "plt.ylabel('Flux intensity')\n",
    "plt.plot(train_data.iloc[0,])\n",
    "plt.plot(train_data.iloc[1,])\n",
    "plt.plot(train_data.iloc[2,])\n",
    "plt.plot(train_data.iloc[3,])\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels_1 = [100,200,300]\n",
    "for i in labels_1:\n",
    "    plt.hist(train_data.iloc[i,:], bins=2000)\n",
    "    plt.title(\"Gaussian Histogram\")\n",
    "    plt.xlabel(\"flux values\")\n",
    "    plt.show()\n",
    "#where exoplanets are not prresent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#where exoplanets are present\n",
    "labels_1 = [16,21,25]\n",
    "for i in labels_1:\n",
    "    plt.hist(train_data.iloc[i,:], bins=2000)\n",
    "    plt.title(\"Gaussian Histogram\")\n",
    "    plt.xlabel(\"flux values\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#data normalization\n",
    "\n",
    "x_train = train_data.drop([\"LABEL\"],axis=1)\n",
    "y_train = train_data[\"LABEL\"]\n",
    "x_test  = test_data.drop([\"LABEL\"],axis=1)\n",
    "y_test  = test_data[\"LABEL\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train = normalized = normalize(x_train)\n",
    "x_test = normalize(x_test)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train = filtered = ndimage.filters.gaussian_filter(x_train, sigma=10)\n",
    "x_test = ndimage.filters.gaussian_filter(x_test, sigma=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "std_scaler = StandardScaler()\n",
    "x_train = scaled = std_scaler.fit_transform(x_train)\n",
    "x_test = std_scaler.fit_transform(x_test)\n",
    "\n",
    "#we use feature scaling so that all the values remain in the comparable range."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#we have too much of rows /columns and features in our data its 5087 rows and 3198 columns . Basically we need to decrease these features\n",
    "#The number of columns/features that we have been working with is huge. We have 5087 rows and 3198 columns in our training dataset. Basically we need to decrease the number of features(Dimentioanlity Reduction) to remove the possibility of Curse of Dimensionality.\n",
    "\n",
    "#For reducing the number of dimensions/features we will use the most popular dimensionality reduction algorithm i.e. PCA(Principal Component Analysis).\n",
    "\n",
    "#To perform PCA we have to choose the number of features/dimensions that we want in our data.\n",
    "#Dimentioanlity reduction\n",
    "from sklearn.decomposition import PCA\n",
    "pca = PCA() \n",
    "x_train = pca.fit_transform(x_train)\n",
    "x_test = pca.transform(x_test)\n",
    "total=sum(pca.explained_variance_)\n",
    "k=0\n",
    "current_variance=0\n",
    "while current_variance/total < 0.90:\n",
    "    current_variance += pca.explained_variance_[k]\n",
    "    k=k+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "37\n"
     ]
    }
   ],
   "source": [
    "print(k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#now late take us k and apply pca on our independent variables\n",
    "\n",
    "pca = PCA(n_components=37)\n",
    "x_train = pca.fit_transform(x_train)\n",
    "x_test = pca.transform(x_test)\n",
    "plt.figure()\n",
    "plt.plot(np.cumsum(pca.explained_variance_ratio_))\n",
    "plt.xlabel('Number of Components')\n",
    "plt.ylabel('Variance (%)')\n",
    "plt.title('Exoplanet Dataset Explained Variance')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5087, 37)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.shap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(570, 37)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#The number of columns got reduced to 37 in both test and train datasets.\n",
    "\n",
    "#Now moving on to the next step, as we know the target class is not equally distributed and one class dominates the other. So we need to resample our data so that the target class is equally distributed.\n",
    "\n",
    "#There are 4 ways of addressing class imbalance problems like these:\n",
    "\n",
    "#Synthesis of new minority class instances\n",
    "#Over-sampling of minority class\n",
    "#Under-sampling of the majority class\n",
    "#Tweak the cost function to make misclassification of minority instances more important than misclassification of majority instances."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before OverSampling, counts of label '1': 37\n",
      "Before OverSampling, counts of label '0': 5050 \n",
      "\n",
      "After OverSampling, counts of label '1': 5050\n",
      "After OverSampling, counts of label '0': 5050\n"
     ]
    }
   ],
   "source": [
    "\n",
    "print(\"Before OverSampling, counts of label '1': {}\".format(sum(y_train==1)))\n",
    "print(\"Before OverSampling, counts of label '0': {} \\n\".format(sum(y_train==0)))\n",
    "sm = SMOTE(random_state=27)\n",
    "x_train_res, y_train_res = sm.fit_sample(x_train, y_train.ravel())\n",
    "print(\"After OverSampling, counts of label '1': {}\".format(sum(y_train_res==1)))\n",
    "print(\"After OverSampling, counts of label '0': {}\".format(sum(y_train_res==0)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "def model (classifier, dtrain_x, dtrain_y, dtest_x, dtest_y):\n",
    "    classifier.fit(dtrain_x, dtrain_y)\n",
    "    predictions = classifier.predict(dtest_x)\n",
    "    \n",
    "    #cross validation\n",
    "    accuracies = cross_val_score(estimator = classifier, X = x_train_res, y= y_train_res, cv = 5, n_jobs = -1)\n",
    "    mean = accuracies.mean()\n",
    "    variance = accuracies.mean()\n",
    "    print(\"Accuracies mean:\" +str(mean))\n",
    "    print(\"Accuracy Variance\" +str(variance))\n",
    "    \n",
    "    \n",
    "    #accuracy\n",
    "    print(\"\\naccuracy_score :\",accuracy_score(dtest_y,predictions))\n",
    "    \n",
    "    #classification report\n",
    "    print(\"\\nclassififcation report :\\n\",(classification_report(dtest_y, predictions)))\n",
    "    \n",
    "    \n",
    "    #confusion matrix\n",
    "    plt.figure(figsize=(13,10))\n",
    "    plt.subplot(221)\n",
    "    sns.heatmap(confusion_matrix(dtest_y,predictions),annot=True,cmap=\"viridis\",fmt=\"d\",linecolor=\"k\",linewidths=3)\n",
    "    plt.title(\"CONFUSION MATRIX\", fontsize=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracies mean:0.9991089108910891\n",
      "Accuracy Variance0.9991089108910891\n",
      "\n",
      "accuracy_score : 0.9912280701754386\n",
      "\n",
      "classififcation report :\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.99      1.00      1.00       565\n",
      "           1       0.00      0.00      0.00         5\n",
      "\n",
      "    accuracy                           0.99       570\n",
      "   macro avg       0.50      0.50      0.50       570\n",
      "weighted avg       0.98      0.99      0.99       570\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.svm import SVC\n",
    "SVM_model=SVC()\n",
    "model(SVM_model,x_train_res,y_train_res,x_test,y_test)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}