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Heart_Stroke_Prediction.ipynb
3251 lines (3251 with data), 550.0 kB
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"-import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns"
]
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"**1 Data Collection -**\n",
"\n"
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"df = pd.read_csv(\"heart_data.csv\",na_values=['?'], low_memory = False)\n",
"df"
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" age sex cp trestbps chol fbs restecg thalach exang oldpeak \\\n",
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"2 41 0 1 130 204 0 0 172 0 1.4 \n",
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"300 68 1 0 144 193 1 1 141 0 3.4 \n",
"301 57 1 0 130 131 0 1 115 1 1.2 \n",
"302 57 0 1 130 236 0 0 174 0 0.0 \n",
"\n",
" slope ca thal target \n",
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{
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"data": {
"text/plain": [
" age sex cp trestbps chol fbs restecg thalach exang oldpeak \\\n",
"298 57 0 0 140 241 0 1 123 1 0.2 \n",
"299 45 1 3 110 264 0 1 132 0 1.2 \n",
"300 68 1 0 144 193 1 1 141 0 3.4 \n",
"301 57 1 0 130 131 0 1 115 1 1.2 \n",
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"\n",
" slope ca thal target \n",
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{
"cell_type": "markdown",
"source": [
"**3. Data Cleaning:-**\n",
"\n",
"\n"
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"metadata": {
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{
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"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 303 entries, 0 to 302\n",
"Data columns (total 14 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 age 303 non-null int64 \n",
" 1 sex 303 non-null int64 \n",
" 2 cp 303 non-null int64 \n",
" 3 trestbps 303 non-null int64 \n",
" 4 chol 303 non-null int64 \n",
" 5 fbs 303 non-null int64 \n",
" 6 restecg 303 non-null int64 \n",
" 7 thalach 303 non-null int64 \n",
" 8 exang 303 non-null int64 \n",
" 9 oldpeak 303 non-null float64\n",
" 10 slope 303 non-null int64 \n",
" 11 ca 303 non-null int64 \n",
" 12 thal 303 non-null int64 \n",
" 13 target 303 non-null int64 \n",
"dtypes: float64(1), int64(13)\n",
"memory usage: 33.3 KB\n"
]
}
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{
"cell_type": "code",
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"df.shape"
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{
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"df.shape"
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"age 0\n",
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"age -0.202463\n",
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"metadata": {},
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"df['thalach'].fillna(df['thalach'].mean(),inplace=True)"
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"metadata": {
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"execution_count": null,
"outputs": []
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{
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"source": [
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"execution_count": null,
"outputs": []
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"text/plain": [
"age 0\n",
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"cp 0\n",
"trestbps 0\n",
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},
"metadata": {},
"execution_count": 25
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{
"cell_type": "code",
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"**4.Feature Selection:-**"
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{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1440x864 with 2 Axes>"
],
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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"df.columns"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "YpuvD-nTOn55",
"outputId": "2ce19b98-4d6b-4059-8349-e7fa0a1209d9"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Index(['age', 'sex', 'cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach',\n",
" 'exang', 'oldpeak', 'slope', 'ca', 'thal', 'target'],\n",
" dtype='object')"
]
},
"metadata": {},
"execution_count": 17
}
]
},
{
"cell_type": "code",
"source": [
"df=df.rename(columns={\"target \":\"target\"})"
],
"metadata": {
"id": "dLXNSlkcOsfH"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df.columns"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "HdPGr5KcOvj5",
"outputId": "98452fcc-c78a-40b8-b86e-054f668723bf"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Index(['age', 'sex', 'cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach',\n",
" 'exang', 'oldpeak', 'slope', 'ca', 'thal', 'target'],\n",
" dtype='object')"
]
},
"metadata": {},
"execution_count": 19
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(12,5))\n",
"plt.title(\"AGE VRS TARGET\")\n",
"sns.distplot(df.age[df.target==0],color=\"darkblue\")\n",
"sns.distplot(df.age[df.target==1],color=\"cyan\")\n",
"plt.legend(['0','1'])\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 439
},
"id": "fxn_S9DeO1tJ",
"outputId": "9f71bfa2-ec72-4f5d-d11e-92f2ff641f6f"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
" warnings.warn(msg, FutureWarning)\n",
"/usr/local/lib/python3.8/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
" warnings.warn(msg, FutureWarning)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 864x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"df.hist()\n",
"plt.figure(figsize=(20,12))\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 298
},
"id": "7LXhvBoOO-p4",
"outputId": "75b2d8df-6f2b-43c3-bc24-71d81f73cc90"
},
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 16 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1440x864 with 0 Axes>"
]
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(12,5))\n",
"plt.title(\"TRESTBPS VRS TARGET\")\n",
"sns.distplot(df.trestbps[df.target==0],color=\"darkblue\")\n",
"sns.distplot(df.trestbps[df.target==1],color=\"cyan\")\n",
"plt.legend(['0','1'])\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 439
},
"id": "nNYf_9VtPC_O",
"outputId": "2bfa031c-59a8-4abe-d26a-ddf0203a83be"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
" warnings.warn(msg, FutureWarning)\n",
"/usr/local/lib/python3.8/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
" warnings.warn(msg, FutureWarning)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 864x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(12,5))\n",
"plt.title(\"CHO VRS TARGET\")\n",
"sns.distplot(df.chol[df.target==0],color=\"darkblue\")\n",
"sns.distplot(df.chol[df.target==1],color=\"cyan\")\n",
"plt.legend(['0','1'])\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 439
},
"id": "KOIiljfUPHn8",
"outputId": "f1c588c9-0384-4c8f-9796-44d18d5b5603"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
" warnings.warn(msg, FutureWarning)\n",
"/usr/local/lib/python3.8/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
" warnings.warn(msg, FutureWarning)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 864x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(12,5))\n",
"plt.title(\"THALACH VRS TARGET\")\n",
"sns.distplot(df.thalach[df.target==0],color=\"darkblue\")\n",
"sns.distplot(df.thalach[df.target==1],color=\"cyan\")\n",
"plt.legend(['0','1'])\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 439
},
"id": "l9j00mHlPLmy",
"outputId": "5d0df887-bf58-46b5-f77c-f5aebb515b89"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
" warnings.warn(msg, FutureWarning)\n",
"/usr/local/lib/python3.8/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
" warnings.warn(msg, FutureWarning)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 864x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(6,3))\n",
"plt.title(\"SEX VRS TARGET\")\n",
"sns.countplot(df.sex)\n",
"plt.show()\n",
"sns.countplot(df.sex[df.target==1])\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 592
},
"id": "JWqKs_ybPPsW",
"outputId": "8b0b3195-9adf-46d1-866b-f83ff240a1da"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x216 with 1 Axes>"
],
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAADgCAYAAADsbXoVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAQeElEQVR4nO3deZQlZX3G8e/DIkZAgcw4AoOOh4MmuKGOCEYTjEYWk2CUICgyKHGMoicaFYknR4iRc4zgghvJENlcEFzBSIKGGDkGUAejyCJmRJZBYIZNVpHBX/641S+XpnvmTsvte6G/n3PqdNVbb9363Z6efrreqluVqkKSJIANRl2AJGl8GAqSpMZQkCQ1hoIkqTEUJEmNoSBJagwFSVJjKGjsJHl+knOT/DLJTUn+J8lzunUHJbk3ye2Tpm2SbJbkiiSv7nutzZNclWSfKfbzz0lOnqL9GUnuTrJVkiOS3NPt45aurl0n9X93kp93fVYmOXWa99Vf72+S3NW3/Oquz25JKsm7Jm27qGuf6H9FksOm2Md+Sb6b5I4kq7r5NyVJt/7EJL+eVMuPkrygb/mOSfu6PcnjB/vX00NeVTk5jc0EPBq4Bdgf2BD4HeAlwNO79QcB31nL9rsDq4H53fKxwJen6bsrcDuw6aT2o4EvdfNHAJ/p5jcCjgRW9vVdAlwKbN8tPw5YOsD7vAJ48RTtJwA3AhdPal8EFLBRt7wYuAP4k74+bweuB/YBNgcCPBP4LLBJ1+dE4H3rqO1++3KaW5NHCho3TwKoqlOq6t6ququqvlFVFw6ycVWdBXwd+GiS3YB9gTdN0/c84BrgFRNtSTYEXgU84AiiqtbQ+wW7bZL5XfNzgLOq6mddn+uqatlA73SSJJvS+4V+CLBDksXT9a2q5cDFwE7dto8B3gu8qaq+WFW3Vc//VtWrq+rumdSkucdQ0Lj5KXBvkpOS7Jlkyxm8xtuA3YAvAu+oquvW0vdk4MC+5RcDGwNnTu6Y5BFd3xuBm7vm84EDk7wzyeIuVGbq5fSOXL4AnEXvKGRKSXYBngqs6Jp2BTYBTv8t9i8ZChovVXUr8Hx6wxfHAauTnJFkQV+3Xbrx/YnpZ5Ne42Z6f0U/CvjyOnb5aeCPkizslg8EPldV9/T12TfJLcBdwOuBfbqjBqrqM8Bb6A1bfRtYNfl8wHpYApxaVfcCnwP2S7LxpD43JLkLOA/4JPDVrn0ecMNEXQDd+Y9bunMXf9j3Gu+Y9P07aYb16mHIUNDYqapLq+qgqlpI76/hbYCP9HU5v6q26Ju2798+yQH0xsX/E/indezrKuAc4IAkmwEv44FDR6dV1RbAAuAi4NmTXuOzVfViYAvgr4F/TLL7+rznJNsBL6Q3PAW9v/gfCbx0Utd5wGb0zh/sRu+oBnpHL/OSbNRX1/O6um/k/v/Xj570/Zv2iERzj6GgsVZVP6F3cvSpg/RP8ljgw/T+on8Dvb/yX7COzU4CXkPv3MLPq+qCaWq5AVgKHJFk6ynW31NVXwAuHLTePq+h9//xa0muAy6nFwoP+IXdnWv5EPAr7jtfch5wN7D3eu5Xuh9DQWMlye8lefvEcE73F/T+9MbuB/Fx4KtV9a2quhY4FDguySZr2eZLwOOBf6AXENOqqsvojfcf2tV3UJKXdpe+bpBkT+ApwHcHrHfCkm7/O/VNrwD2SvK702zzfuDQJI+sqlu67T+ZZJ++enYCNl3PWjSHGQoaN7cBzwW+m+QOemFwEb3hkgm7TvE5heckeRm98xHvnOhYVf8K/AJ4z3Q7rKo76AXDQu4bvlmbo4Cl3VHJrcC7gavoXUr7AeCNVfWdQd9wd9L4CcAnuquXJqYz6J1I3n+aTb9O74T367v38QHgb+kF1vXd9C/Au4Bz+7Y7dNL37oZBa9XDX6p8yI4kqccjBUlSYyhIkhpDQZLUGAqSpMZQkCQ1G627y/iaN29eLVq0aNRlSNJDygUXXHBDVc2fat1DOhQWLVrE8uXLR12GJD2kJLlyunUOH0mSGkNBktQYCpKkxlCQJDWGgiSpeUhffSQ9nF313qeNugSNoce/58dDfX2PFCRJzdBCIcl2Sb6V5JIkFyf5m659qyTfTPJ/3dctu/Yk+WiSFUkuTPKsYdUmSZraMI8U1gBvr6odgV2AQ5LsCBwGnF1VOwBnd8sAewI7dNNS4Ngh1iZJmsLQQqGqrq2qH3TztwGXAtvSe4bsxCMPT6L3oHS69pOr53xgi6megytJGp5ZOaeQZBHwTHrPrV3QPTsX4DpgQTe/LXB132YruzZJ0iwZeigk2Yze82/fWlW39q+r3rNA1+t5oEmWJlmeZPnq1asfxEolSUMNhSQb0wuEz1bVl7vm6yeGhbqvq7r2a4Dt+jZf2LXdT1Utq6rFVbV4/vwpb/InSZqhYV59FOBTwKVV9aG+VWcAS7r5JcDpfe0Hdlch7QL8sm+YSZI0C4b54bU/AF4D/DjJD7u2dwPvB05LcjBwJbBvt+5MYC9gBXAn8Noh1iZJmsLQQqGqvgNkmtUvmqJ/AYcMqx5J0rr5iWZJUmMoSJIaQ0GS1BgKkqTGUJAkNYaCJKkxFCRJjaEgSWoMBUlSYyhIkhpDQZLUGAqSpMZQkCQ1hoIkqTEUJEmNoSBJagwFSVJjKEiSGkNBktQYCpKkxlCQJDWGgiSpMRQkSY2hIElqDAVJUmMoSJIaQ0GS1BgKkqTGUJAkNUMLhSTHJ1mV5KK+tiOSXJPkh920V9+6v0uyIsllSXYfVl2SpOkN80jhRGCPKdo/XFU7ddOZAEl2BPYDntJt88kkGw6xNknSFIYWClV1DnDTgN33Bj5fVXdX1c+BFcDOw6pNkjS1UZxTeHOSC7vhpS27tm2Bq/v6rOzaHiDJ0iTLkyxfvXr1sGuVpDlltkPhWGB7YCfgWuCD6/sCVbWsqhZX1eL58+c/2PVJ0pw2q6FQVddX1b1V9RvgOO4bIroG2K6v68KuTZI0i2Y1FJJs3bf4F8DElUlnAPsl2STJE4EdgO/NZm2SJNhoWC+c5BRgN2BekpXA4cBuSXYCCrgCeANAVV2c5DTgEmANcEhV3Tus2iRJUxtaKFTV/lM0f2ot/Y8EjhxWPZKkdfMTzZKkxlCQJDWGgiSpMRQkSY2hIElqDAVJUmMoSJIaQ0GS1BgKkqTGUJAkNYaCJKkxFCRJjaEgSWoMBUlSM1AoJDl7kDZJ0kPbWp+nkOSRwKPoPShnSyDdqkcD2w65NknSLFvXQ3beALwV2Aa4gPtC4Vbg40OsS5I0AmsNhao6BjgmyVuq6mOzVJMkaUQGehxnVX0syfOARf3bVNXJQ6pLkjQCA4VCkk8D2wM/BO7tmgswFCTpYWSgUAAWAztWVQ2zGEnSaA36OYWLgMcNsxBJ0ugNeqQwD7gkyfeAuycaq+rPh1KVJGkkBg2FI4ZZhCRpPAx69dG3h12IJGn0Br366DZ6VxsBPALYGLijqh49rMIkSbNv0COFzSfmkwTYG9hlWEVJkkZjve+SWj1fBXYfQj2SpBEadPjo5X2LG9D73MKv1rHN8cCfAquq6qld21bAqfQ+GX0FsG9V3dwdfRwD7AXcCRxUVT9Yr3ciSfqtDXqk8Gd90+7AbfSGkNbmRGCPSW2HAWdX1Q7A2d0ywJ7ADt20FDh2wLokSQ+iQc8pvHZ9X7iqzkmyaFLz3sBu3fxJwH8D7+raT+4+MX1+ki2SbF1V167vfiVJMzfoQ3YWJvlKklXd9KUkC2ewvwV9v+ivAxZ089sCV/f1W4nPa5CkWTfo8NEJwBn0nquwDfC1rm3GuqOC9b6XUpKlSZYnWb569erfpgRJ0iSDhsL8qjqhqtZ004nA/Bns7/okWwN0X1d17dcA2/X1W9i1PUBVLauqxVW1eP78mZQgSZrOoKFwY5IDkmzYTQcAN85gf2cAS7r5JcDpfe0HpmcX4JeeT5Ck2TfovY9eB3wM+DC9IZ9zgYPWtkGSU+idVJ6XZCVwOPB+4LQkBwNXAvt23c+kdznqCnqXpK73ie2ZevY7fSSEHuiCow4cdQnSSAwaCu8FllTVzdA+b3A0vbCYUlXtP82qF03Rt4BDBqxFkjQkgw4fPX0iEACq6ibgmcMpSZI0KoOGwgZJtpxY6I4UBj3KkCQ9RAz6i/2DwHlJvtAt/yVw5HBKkiSNyqCfaD45yXLgj7uml1fVJcMrS5I0CgMPAXUhYBBI0sPYet86W5L08GUoSJIaQ0GS1BgKkqTGUJAkNYaCJKkxFCRJjaEgSWoMBUlSYyhIkhpDQZLUGAqSpMZQkCQ1hoIkqTEUJEmNoSBJagwFSVJjKEiSGkNBktQYCpKkxlCQJDWGgiSpMRQkSY2hIElqNhrFTpNcAdwG3AusqarFSbYCTgUWAVcA+1bVzaOoT5LmqlEeKbywqnaqqsXd8mHA2VW1A3B2tyxJmkXjNHy0N3BSN38S8LIR1iJJc9KoQqGAbyS5IMnSrm1BVV3bzV8HLJhqwyRLkyxPsnz16tWzUaskzRkjOacAPL+qrknyWOCbSX7Sv7KqKklNtWFVLQOWASxevHjKPpKkmRnJkUJVXdN9XQV8BdgZuD7J1gDd11WjqE2S5rJZD4UkmybZfGIeeAlwEXAGsKTrtgQ4fbZrk6S5bhTDRwuArySZ2P/nquo/knwfOC3JwcCVwL4jqE2S5rRZD4Wquhx4xhTtNwIvmu16JEn3GadLUiVJI2YoSJIaQ0GS1BgKkqTGUJAkNYaCJKkxFCRJjaEgSWoMBUlSYyhIkhpDQZLUGAqSpMZQkCQ1hoIkqTEUJEmNoSBJagwFSVJjKEiSGkNBktQYCpKkxlCQJDWGgiSpMRQkSY2hIElqDAVJUmMoSJIaQ0GS1BgKkqRm7EIhyR5JLkuyIslho65HkuaSsQqFJBsCnwD2BHYE9k+y42irkqS5Y6xCAdgZWFFVl1fVr4HPA3uPuCZJmjPGLRS2Ba7uW17ZtUmSZsFGoy5gfSVZCiztFm9Pctko63mYmQfcMOoixkGOXjLqEnR//mxOODwPxqs8YboV4xYK1wDb9S0v7NqaqloGLJvNouaKJMuravGo65Am82dz9ozb8NH3gR2SPDHJI4D9gDNGXJMkzRljdaRQVWuSvBk4C9gQOL6qLh5xWZI0Z4xVKABU1ZnAmaOuY45yWE7jyp/NWZKqGnUNkqQxMW7nFCRJI2QoyFuLaGwlOT7JqiQXjbqWucJQmOO8tYjG3InAHqMuYi4xFOStRTS2quoc4KZR1zGXGAry1iKSGkNBktQYClrnrUUkzR2Ggry1iKTGUJjjqmoNMHFrkUuB07y1iMZFklOA84AnJ1mZ5OBR1/Rw5yeaJUmNRwqSpMZQkCQ1hoIkqTEUJEmNoSBJagwFSVJjKEiSGkNBmqEkmyb5epIfJbkoySuTPDvJt5NckOSsJFsneUz3vIond9udkuT1o65fmsrYPaNZegjZA/hFVb0UIMljgH8H9q6q1UleCRxZVa9L8mbgxCTHAFtW1XGjK1uanp9olmYoyZOAbwCnAv8G3AycC1zeddkQuLaqXtL1Xwa8AnhGVa2c/YqldfNIQZqhqvppkmcBewHvA/4LuLiqdp3cN8kGwO8DdwJb0ntuhTR2PKcgzVCSbYA7q+ozwFHAc4H5SXbt1m+c5Cld97fRu+Hgq4ATkmw8ipqldfFIQZq5pwFHJfkNcA/wRmAN8NHu/MJGwEeSrAH+Cti5qm5Lcg7w98DhI6pbmpbnFCRJjcNHkqTGUJAkNYaCJKkxFCRJjaEgSWoMBUlSYyhIkhpDQZLU/D99sHbFt4q+9gAAAABJRU5ErkJggg==\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
],
"image/png": "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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(6,3))\n",
"plt.title(\"CP VRS TARGET\")\n",
"sns.countplot(df.cp)\n",
"plt.show()\n",
"sns.countplot(df.cp[df.target==1])\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 592
},
"id": "cysVSf2ZPzqM",
"outputId": "a7170ea1-55c5-4ea7-be8b-c56a5f875c2f"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x216 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(6,3))\n",
"plt.title(\"FBS VRS TARGET\")\n",
"sns.countplot(df.fbs)\n",
"plt.show()\n",
"sns.countplot(df.fbs[df.target==1])\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 592
},
"id": "JQrShdLdP2IK",
"outputId": "75c1af14-7b75-4793-8b7d-b2f0e4f068d2"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x216 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
],
"image/png": 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e5E/7ziMdKktBOjSvAX4DuLPvINJSsBSkg5Tk74FfAD4NvAF4VpIbktyZ5A+6fU5Icn2SW5JsT/JrfWaWDsSL16RDkORrwAyDq8J/BzgVeDzwReA5wNnAUVV1QffbFUdX1bd7iisd0Iq+A0iHkWuq6vvA95Ncx+C3Kj4PXJLkscAnq+qWXhNKB+DhI2np7D/tru5HYp7H4M6zlyY5Z/yxpOFZCtLSWZ/kqCRPBJ4PfD7Jk4EHquqDwIeAk/sMKB2Ih4+kpXMrcB2wEvjLqvrPJBuANyf5H+A7gDMFLWueaJYkNR4+kiQ1loIkqbEUJEmNpSBJaiwFSVJjKUiSGktBktT8H7TKjCoNn9VNAAAAAElFTkSuQmCC\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(6,3))\n",
"plt.title(\"RESTECG VRS TARGET\")\n",
"sns.countplot(df.restecg)\n",
"plt.show()\n",
"sns.countplot(df.restecg[df.target==1])\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 595
},
"id": "tX0ce5yPP8PL",
"outputId": "9c7e5bfe-23b6-4f4f-d392-a8bc3df45604"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x216 with 1 Axes>"
],
"image/png": "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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
],
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEJCAYAAAB7UTvrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAO/ElEQVR4nO3dcayddX3H8fdHClMQFOwdKy2zRBiuwS2wq2HrZlTQKW5CjEPJ1KokXTanMpZNtrixmS3T6HSMbcZGxLIZFFEHc0bHOtwyhpVbZFJa0YaJFou9KALinHZ+98d5+vPa3dZT7DnPac/7ldzc8zznOeULJ/Sd3znneU6qCkmSAB7V9wCSpMlhFCRJjVGQJDVGQZLUGAVJUmMUJEnNyKKQ5N1JdibZvGDfcUluSPL57vex3f4k+csk25J8JskZo5pLkrR3o1wpvAd47h77LgE2VNUpwIZuG+B5wCndz1rgHSOcS5K0FxnlyWtJVgIfqarTuu07gWdU1Y4ky4BPVNWpSd7Z3b56z+P29ecvXbq0Vq5cObL5JelQtGnTpvuqamax+5aMeZbjF/xFfy9wfHd7OfClBcdt7/btMworV65kbm7ugA8pSYeyJHfv7b7e3miuwRJlv5cpSdYmmUsyNz8/P4LJJGl6jTsKX+leNqL7vbPbfw9w4oLjVnT7/p+qWldVs1U1OzOz6OpHkvQIjTsK1wNruttrgOsW7H959ymkM4EHftD7CZKkA29k7ykkuRp4BrA0yXbgUuBNwDVJLgTuBs7vDv8ocA6wDfgm8MpRzSVJ2ruRRaGqLtjLXWctcmwBrx7VLJKk4XhGsySpMQqSpMYoSJIaoyBJasZ9RrP0iHzxjU/pe4RD3o//4e19j6AJ4EpBktQYBUlSYxQkSY1RkCQ1RkGS1BgFSVJjFCRJjVGQJDVGQZLUGAVJUmMUJEmNUZAkNUZBktQYBUlSYxQkSY1RkCQ1RkGS1BgFSVJjFCRJjVGQJDVGQZLUGAVJUmMUJEmNUZAkNUZBktQYBUlSYxQkSY1RkCQ1RkGS1PQShSS/leSOJJuTXJ3k0UlOSrIxybYk709yRB+zSdI0G3sUkiwHXgvMVtVpwGHAS4A3A2+vqpOB+4ELxz2bJE27vl4+WgI8JskS4EhgB/As4Nru/vXAeT3NJklTa+xRqKp7gLcCX2QQgweATcDXq2pXd9h2YPm4Z5OkadfHy0fHAucCJwEnAEcBz92Px69NMpdkbn5+fkRTStJ06uPlo7OB/6qq+ar6DvAhYDXw+O7lJIAVwD2LPbiq1lXVbFXNzszMjGdiSZoSfUThi8CZSY5MEuAsYAtwI/Ci7pg1wHU9zCZJU62P9xQ2MnhD+Vbg9m6GdcDrgYuTbAOeAFwx7tkkadot+cGHHHhVdSlw6R677wKe1sM4kqSOZzRLkhqjIElqjIIkqTEKkqTGKEiSGqMgSWqMgiSpMQqSpMYoSJIaoyBJaoyCJKkxCpKkxihIkhqjIElqjIIkqTEKkqTGKEiSGqMgSWqMgiSpMQqSpMYoSJKaJX0PMC4/8ztX9T3CVNj0lpf3PYKkH4IrBUlSYxQkSY1RkCQ1RkGS1BgFSVJjFCRJjVGQJDVGQZLUGAVJUmMUJEmNUZAkNUZBktT0EoUkj09ybZLPJtma5GeTHJfkhiSf734f28dskjTN+lopXAZ8rKqeDPw0sBW4BNhQVacAG7ptSdIYjT0KSR4HPB24AqCqvl1VXwfOBdZ3h60Hzhv3bJI07fpYKZwEzANXJvl0knclOQo4vqp2dMfcCxzfw2ySNNX6iMIS4AzgHVV1OvAwe7xUVFUF1GIPTrI2yVySufn5+ZEPK0nTpI8obAe2V9XGbvtaBpH4SpJlAN3vnYs9uKrWVdVsVc3OzMyMZWBJmhZjj0JV3Qt8Kcmp3a6zgC3A9cCabt8a4LpxzyZJ066v72h+DfDeJEcAdwGvZBCoa5JcCNwNnN/TbJI0tXqJQlXdBswuctdZ455FkvQ9ntEsSWqMgiSpMQqSpMYoSJKaoaKQZMMw+yRJB7d9fvooyaOBI4Gl3VVL0911DLB8xLNJksbsB30k9deAi4ATgE18LwoPAn81wrkkST3YZxSq6jLgsiSvqarLxzSTJKknQ528VlWXJ/k5YOXCx1TVVSOaS5LUg6GikORvgScBtwH/2+0uwChI0iFk2MtczAKruktaS5IOUcOep7AZ+LFRDiJJ6t+wK4WlwJYknwL+Z/fOqnrBSKaSJPVi2Cj80SiHkCRNhmE/ffSvox5EktS/YT999BDf+87kI4DDgYer6phRDSZJGr9hVwpH776dJMC5wJmjGkqS1I/9vkpqDfw98IsjmEeS1KNhXz564YLNRzE4b+FbI5lIktSbYT999MsLbu8CvsDgJSRJ0iFk2PcUXjnqQSRJ/Rv2S3ZWJPlwkp3dzweTrBj1cJKk8Rr2jeYrgesZfK/CCcA/dPskSYeQYaMwU1VXVtWu7uc9wMwI55Ik9WDYKHw1yUuTHNb9vBT46igHkySN37BReBVwPnAvsAN4EfCKEc0kSerJsB9JfSOwpqruB0hyHPBWBrGQJB0ihl0p/NTuIABU1deA00czkiSpL8NG4VFJjt290a0Uhl1lSJIOEsP+xf7nwM1JPtBt/wrwp6MZSZLUl2HPaL4qyRzwrG7XC6tqy+jGkiT1YeiXgLoIGAJJOoTt96WzJUmHLqMgSWqMgiSp6S0K3eUyPp3kI932SUk2JtmW5P1JjuhrNkmaVn2uFF4HbF2w/Wbg7VV1MnA/cGEvU0nSFOslCt13MTwfeFe3HQYfd722O2Q9cF4fs0nSNOtrpfAXwO8C3+22nwB8vap2ddvbgeV9DCZJ02zsUUjyS8DOqtr0CB+/Nslckrn5+fkDPJ0kTbc+VgqrgRck+QLwPgYvG10GPD7J7pPpVgD3LPbgqlpXVbNVNTsz4/f8SNKBNPYoVNXvVdWKqloJvAT4l6r6VeBGBt/TALAGuG7cs0nStJuk8xReD1ycZBuD9xiu6HkeSZo6vV7+uqo+AXyiu30X8LQ+55GkaTdJKwVJUs+MgiSpMQqSpMYoSJIaoyBJaoyCJKkxCpKkxihIkhqjIElqjIIkqTEKkqTGKEiSGqMgSWqMgiSpMQqSpMYoSJIaoyBJaoyCJKkxCpKkxihIkhqjIElqjIIkqTEKkqTGKEiSGqMgSWqMgiSpMQqSpMYoSJIaoyBJaoyCJKkxCpKkxihIkhqjIElqjIIkqRl7FJKcmOTGJFuS3JHkdd3+45LckOTz3e9jxz2bJE27PlYKu4DfrqpVwJnAq5OsAi4BNlTVKcCGbluSNEZjj0JV7aiqW7vbDwFbgeXAucD67rD1wHnjnk2Spl2v7ykkWQmcDmwEjq+qHd1d9wLH9zSWJE2t3qKQ5LHAB4GLqurBhfdVVQG1l8etTTKXZG5+fn4Mk0rS9OglCkkOZxCE91bVh7rdX0myrLt/GbBzscdW1bqqmq2q2ZmZmfEMLElToo9PHwW4AthaVW9bcNf1wJru9hrgunHPJknTbkkP/8zVwMuA25Pc1u37feBNwDVJLgTuBs7vYTZJmmpjj0JV/TuQvdx91jhnkSR9P89oliQ1RkGS1BgFSVJjFCRJjVGQJDVGQZLUGAVJUmMUJEmNUZAkNUZBktQYBUlSYxQkSY1RkCQ1RkGS1BgFSVJjFCRJjVGQJDVGQZLUGAVJUmMUJEmNUZAkNUZBktQYBUlSYxQkSY1RkCQ1RkGS1BgFSVJjFCRJjVGQJDVGQZLUGAVJUmMUJEmNUZAkNUZBktRMVBSSPDfJnUm2Jbmk73kkadpMTBSSHAb8NfA8YBVwQZJV/U4lSdNlSd8DLPA0YFtV3QWQ5H3AucCWXqeS9ENZffnqvkeYCje95qYD8udMzEoBWA58acH29m6fJGlMJmmlMJQka4G13eY3ktzZ5zwjthS4r+8h9kfeuqbvESbFQffccWn6nmCSHHTPX167X8/fE/d2xyRF4R7gxAXbK7p936eq1gHrxjVUn5LMVdVs33No//ncHdym+fmbpJePbgFOSXJSkiOAlwDX9zyTJE2ViVkpVNWuJL8JfBw4DHh3Vd3R81iSNFUmJgoAVfVR4KN9zzFBpuJlskOUz93BbWqfv1RV3zNIkibEJL2nIEnqmVGYQF7u4+CV5N1JdibZ3Pcs2n9JTkxyY5ItSe5I8rq+Zxo3Xz6aMN3lPj4HPJvBCXy3ABdUlWd2HwSSPB34BnBVVZ3W9zzaP0mWAcuq6tYkRwObgPOm6f8/VwqTp13uo6q+Dey+3IcOAlX1b8DX+p5Dj0xV7aiqW7vbDwFbmbIrKxiFyePlPqQJkGQlcDqwsd9JxssoSNIekjwW+CBwUVU92Pc842QUJs9Ql/uQNBpJDmcQhPdW1Yf6nmfcjMLk8XIfUk+SBLgC2FpVb+t7nj4YhQlTVbuA3Zf72Apc4+U+Dh5JrgZuBk5Nsj3JhX3PpP2yGngZ8Kwkt3U/5/Q91Dj5kVRJUuNKQZLUGAVJUmMUJEmNUZAkNUZBktQYBekASnJRkiP7nkN6pPxIqrQP3clMqarvDnn8F4DZqrpvpINJI+JKQdpDkpXd91lcBWwG/iDJLUk+k+SPu2OOSvKPSf4zyeYkL07yWuAE4MYkN3bHPSfJzUluTfKB7po6JHlqkv/oHv+pJEcnOTLJNd21/D+cZGOS2b7+O2g6TdR3NEsT5BRgDXAM8CIGlzQPcH33nQkzwJer6vkASR5XVQ8kuRh4ZlXdl2Qp8Abg7Kp6OMnrgYuTvAl4P/DiqrolyTHAfwMXAfdX1aokpwG3jfdfWXKlIO3N3VX1SeA53c+ngVuBJzMIxu3As5O8OckvVNUDi/wZZwKrgJuS3MYgMk8ETgV2VNUtAFX1YHd5k59n8P0ZVNVm4DOj/BeUFuNKQVrcw93vAH9WVe/c84AkZwDnAH+SZENVvXHPQ4AbquqCPR73lFEMLB0IrhSkffs48KoF7wUsT/KjSU4AvllVfwe8BTijO/4h4Oju9ieB1UlO7h57VJKfAO4EliV5arf/6CRLgJuA87t9qwDjobFzpSDtQ1X9U5KfBG4efBCJbwAvBU4G3pLku8B3gF/vHrIO+FiSL1fVM5O8Arg6yY9097+hqj6X5MXA5Ukew+D9hLOBvwHWJ9kCfBa4A1jsZSlpZPxIqjQhkhwGHF5V30ryJOCfgVO77+qWxsKVgjQ5jmTwcdbDGbwf8RsGQePmSkGS1PhGsySpMQqSpMYoSJIaoyBJaoyCJKkxCpKk5v8AgfWE27v3F+EAAAAASUVORK5CYII=\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(6,3))\n",
"plt.title(\"EXANG VRS TARGET\")\n",
"sns.countplot(df.exang)\n",
"plt.show()\n",
"sns.countplot(df.exang[df.target==1])\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 592
},
"id": "kw_pNfHHP_RJ",
"outputId": "cbe8cc52-1825-46b1-a2b1-f84a38479882"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x216 with 1 Axes>"
],
"image/png": "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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
],
"image/png": "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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(6,3))\n",
"plt.title(\"SLOPE VRS TARGET\")\n",
"sns.countplot(df.slope)\n",
"plt.show()\n",
"sns.countplot(df.slope[df.target==1])\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 592
},
"id": "Q5WRtcQTQCMd",
"outputId": "89de8f80-6f4c-411b-ced4-36f55131d4ed"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x216 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
],
"image/png": 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JatxTkCQ1RkGS1BgFSVJjFCRJjVGQJDX/C8aaQeuQ3cd7AAAAAElFTkSuQmCC\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(6,3))\n",
"plt.title(\"THAL VRS TARGET\")\n",
"sns.countplot(df.thal)\n",
"plt.show()\n",
"sns.countplot(df.thal[df.target==1])\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 592
},
"id": "Quu2ua5xQE8X",
"outputId": "ac4a2538-d1c3-4010-8e33-d19e6fd449f5"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x216 with 1 Axes>"
],
"image/png": "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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
],
"image/png": "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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(12,5))\n",
"plt.title(\"SEX VRS AGE VRS TARGET\")\n",
"sns.pointplot(x = 'sex',y='age',hue='target',data=df)\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 350
},
"id": "CMQU1YnJQR5n",
"outputId": "aaf20de5-f860-4839-d556-5ac1297f60be"
},
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 864x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(12,5))\n",
"plt.title(\"CHOL VRS AGE VRS TARGET\")\n",
"sns.scatterplot(x='chol',y='age',hue='target',data=df)\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 350
},
"id": "lAg-gEC6QZh9",
"outputId": "0a580d66-f366-45c5-e055-c745482d5e43"
},
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 864x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"**5 Split the data into train and test set:-**"
],
"metadata": {
"id": "fvF5RvEDRXoj"
}
},
{
"cell_type": "code",
"source": [
"x=df[['age', 'sex', 'cp','trestbps', 'chol', 'fbs','restecg', 'thalach', 'exang', 'oldpeak', 'slope','thal']]\n",
"y=df['target']\n",
"print(x)\n",
"print(y)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "1HYoi7L1Qc1m",
"outputId": "98a564df-e87b-4bb2-9985-2e3f946635f7"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" age sex cp trestbps chol fbs restecg thalach exang oldpeak \\\n",
"0 63 1 3 145 233 1 0 150 0 2.3 \n",
"1 37 1 2 130 250 0 1 187 0 3.5 \n",
"2 41 0 1 130 204 0 0 172 0 1.4 \n",
"3 56 1 1 120 236 0 1 178 0 0.8 \n",
"4 57 0 0 120 354 0 1 163 1 0.6 \n",
".. ... ... .. ... ... ... ... ... ... ... \n",
"298 57 0 0 140 241 0 1 123 1 0.2 \n",
"299 45 1 3 110 264 0 1 132 0 1.2 \n",
"300 68 1 0 144 193 1 1 141 0 3.4 \n",
"301 57 1 0 130 131 0 1 115 1 1.2 \n",
"302 57 0 1 130 236 0 0 174 0 0.0 \n",
"\n",
" slope thal \n",
"0 0 1 \n",
"1 0 2 \n",
"2 2 2 \n",
"3 2 2 \n",
"4 2 2 \n",
".. ... ... \n",
"298 1 3 \n",
"299 1 3 \n",
"300 1 3 \n",
"301 1 3 \n",
"302 1 2 \n",
"\n",
"[303 rows x 12 columns]\n",
"0 1\n",
"1 1\n",
"2 1\n",
"3 1\n",
"4 1\n",
" ..\n",
"298 0\n",
"299 0\n",
"300 0\n",
"301 0\n",
"302 0\n",
"Name: target, Length: 303, dtype: int64\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"# split data into train and test\n",
"from sklearn.model_selection import train_test_split\n",
"xtr,xts,ytr,yts = train_test_split(x,y,test_size=0.2)\n",
"# we have to split the data into 80% as train and 20% as test so we have specified test_size as 0.2\n",
"print(x.shape)\n",
"print(xtr.shape)\n",
"print(xts.shape)\n",
"print(y.shape)\n",
"print(ytr.shape)\n",
"print(yts.shape)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "7oGMz2-GRjfi",
"outputId": "b0bf471d-f5a3-49cc-f805-d5c62ed20310"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(303, 12)\n",
"(242, 12)\n",
"(61, 12)\n",
"(303,)\n",
"(242,)\n",
"(61,)\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"from sklearn.decomposition import PCA\n",
"pca = PCA(n_components = 1)\n",
"xtr = pca.fit_transform(xtr)\n",
"xts = pca.transform(xts)\n",
"explained_variance = pca.explained_variance_ratio_"
],
"metadata": {
"id": "gJJnOeyIRuoc"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"**SVM**"
],
"metadata": {
"id": "EEeCkqSuR56Y"
}
},
{
"cell_type": "code",
"source": [
"from sklearn.svm import SVC"
],
"metadata": {
"id": "ltdoc-hlRyxV"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from sklearn.metrics import classification_report,confusion_matrix"
],
"metadata": {
"id": "u00XYWyoSE_u"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"svc_model=SVC()"
],
"metadata": {
"id": "CpfiMQGeSLTu"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"svc_model.fit(xtr,ytr)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "UN4ch_LySOOK",
"outputId": "19f354a5-edd4-4831-bce3-517ecaa33b46"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"SVC()"
]
},
"metadata": {},
"execution_count": 42
}
]
},
{
"cell_type": "code",
"source": [
"y_pred=svc_model.predict(xts)"
],
"metadata": {
"id": "8ZiEnDwHSSK_"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"cm=confusion_matrix(yts,y_pred)"
],
"metadata": {
"id": "-IPvPrzrSVXw"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"sns.heatmap(cm,annot=True)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 282
},
"id": "i7gvwP_ZSeFl",
"outputId": "e0c17fc5-679c-49ed-8d15-5f5dc0ba3935"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f070d528880>"
]
},
"metadata": {},
"execution_count": 45
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
],
"image/png": "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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"**Normalisation(1):-**"
],
"metadata": {
"id": "Mm-X_qn4Sv49"
}
},
{
"cell_type": "code",
"source": [
"min_train = xtr.min()\n",
"min_train"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "q8oDTyQDShly",
"outputId": "7cf0ddda-59e7-49db-bd5e-e047f39de246"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"-116.0867252484349"
]
},
"metadata": {},
"execution_count": 46
}
]
},
{
"cell_type": "code",
"source": [
"range_train = (xtr - min_train).max()\n",
"range_train"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "d7UEMDYSS5BA",
"outputId": "eb8aaed8-0a1d-4d6b-b36b-7c2c9f01e868"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"432.16460507980736"
]
},
"metadata": {},
"execution_count": 47
}
]
},
{
"cell_type": "code",
"source": [
"X_train_scaled = (xtr - min_train)/range_train\n",
"X_train_scaled"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "SQ8a6SMqS8fO",
"outputId": "c93e4a4d-6d79-49d0-ace4-447394d25b8e"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([[0.27221444],\n",
" [0.15254557],\n",
" [0.30125771],\n",
" [0.43523688],\n",
" [0.14575809],\n",
" [0.22659942],\n",
" [0.21982852],\n",
" [0.15126453],\n",
" [0.20939863],\n",
" [0.32314495],\n",
" [0.17364738],\n",
" [0.17827498],\n",
" [0.14979229],\n",
" [0.3422074 ],\n",
" [0.27729965],\n",
" [0.31369478],\n",
" [0.03976612],\n",
" [0.18774677],\n",
" [0.26300267],\n",
" [0.3646504 ],\n",
" [0.32287946],\n",
" [0.20692056],\n",
" [0.3995374 ],\n",
" [0.21365344],\n",
" [0.12627063],\n",
" [0.34678383],\n",
" [0.29125925],\n",
" [0.32483618],\n",
" [0.28229808],\n",
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" [0.20069718]])"
]
},
"metadata": {},
"execution_count": 48
}
]
},
{
"cell_type": "code",
"source": [
"min_test = xts.min()\n",
"range_test = (xts - min_test).max()\n",
"X_test_scaled = (xts - min_test)/range_test"
],
"metadata": {
"id": "0IJdeMqcS_Jd"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from sklearn.svm import SVC\n",
"from sklearn.metrics import classification_report, confusion_matrix\n",
"\n",
"svc_model = SVC()\n",
"svc_model.fit(X_train_scaled, ytr)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "_g6ykxk6TJqf",
"outputId": "da6f6e09-4aa0-4e50-cb66-0c813d1a0a60"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"SVC()"
]
},
"metadata": {},
"execution_count": 50
}
]
},
{
"cell_type": "code",
"source": [
"y_predict = svc_model.predict(X_test_scaled)\n",
"cm = confusion_matrix(yts, y_predict)\n",
"\n",
"sns.heatmap(cm,annot=True,fmt=\"d\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 282
},
"id": "WCd8GwIHTMzT",
"outputId": "cf36fa42-b4f0-49bc-b65d-a3e4a60b08e7"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f070d236af0>"
]
},
"metadata": {},
"execution_count": 51
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
],
"image/png": "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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"print(classification_report(yts,y_predict))\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "fZe9uo0LTQep",
"outputId": "d1a766fb-34f4-4dfe-f7db-1a5e5f24e09c"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.39 0.26 0.31 27\n",
" 1 0.53 0.68 0.60 34\n",
"\n",
" accuracy 0.49 61\n",
" macro avg 0.46 0.47 0.45 61\n",
"weighted avg 0.47 0.49 0.47 61\n",
"\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"**Normalisation(2):-**"
],
"metadata": {
"id": "NNCjgjV9Tc-M"
}
},
{
"cell_type": "code",
"source": [
"param_grid = {'C': [0.1, 1, 10, 100], 'gamma': [1, 0.1, 0.01, 0.001], 'kernel': ['rbf']}"
],
"metadata": {
"id": "2eFVnJyqTX5j"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from sklearn.model_selection import GridSearchCV\n",
"grid = GridSearchCV(SVC(),param_grid,refit=True,verbose=4)\n",
"grid.fit(X_train_scaled,ytr)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "_jUAl9X7Tj95",
"outputId": "009c7da6-a8b5-455a-bbf8-afc9bc498355"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Fitting 5 folds for each of 16 candidates, totalling 80 fits\n",
"[CV 1/5] END ........C=0.1, gamma=1, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END ........C=0.1, gamma=1, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END ........C=0.1, gamma=1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END ........C=0.1, gamma=1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END ........C=0.1, gamma=1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END ......C=0.1, gamma=0.1, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END ......C=0.1, gamma=0.1, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END ......C=0.1, gamma=0.1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END ......C=0.1, gamma=0.1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END ......C=0.1, gamma=0.1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END .....C=0.1, gamma=0.01, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END .....C=0.1, gamma=0.01, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END .....C=0.1, gamma=0.01, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END .....C=0.1, gamma=0.01, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END .....C=0.1, gamma=0.01, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END ....C=0.1, gamma=0.001, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END ....C=0.1, gamma=0.001, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END ....C=0.1, gamma=0.001, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END ....C=0.1, gamma=0.001, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END ....C=0.1, gamma=0.001, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END ..........C=1, gamma=1, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END ..........C=1, gamma=1, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END ..........C=1, gamma=1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END ..........C=1, gamma=1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END ..........C=1, gamma=1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END ........C=1, gamma=0.1, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END ........C=1, gamma=0.1, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END ........C=1, gamma=0.1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END ........C=1, gamma=0.1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END ........C=1, gamma=0.1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END .......C=1, gamma=0.01, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END .......C=1, gamma=0.01, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END .......C=1, gamma=0.01, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END .......C=1, gamma=0.01, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END .......C=1, gamma=0.01, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END ......C=1, gamma=0.001, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END ......C=1, gamma=0.001, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END ......C=1, gamma=0.001, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END ......C=1, gamma=0.001, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END ......C=1, gamma=0.001, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END .........C=10, gamma=1, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END .........C=10, gamma=1, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END .........C=10, gamma=1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END .........C=10, gamma=1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END .........C=10, gamma=1, kernel=rbf;, score=0.521 total time= 0.0s\n",
"[CV 1/5] END .......C=10, gamma=0.1, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END .......C=10, gamma=0.1, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END .......C=10, gamma=0.1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END .......C=10, gamma=0.1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END .......C=10, gamma=0.1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END ......C=10, gamma=0.01, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END ......C=10, gamma=0.01, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END ......C=10, gamma=0.01, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END ......C=10, gamma=0.01, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END ......C=10, gamma=0.01, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END .....C=10, gamma=0.001, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END .....C=10, gamma=0.001, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END .....C=10, gamma=0.001, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END .....C=10, gamma=0.001, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END .....C=10, gamma=0.001, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END ........C=100, gamma=1, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END ........C=100, gamma=1, kernel=rbf;, score=0.571 total time= 0.0s\n",
"[CV 3/5] END ........C=100, gamma=1, kernel=rbf;, score=0.604 total time= 0.0s\n",
"[CV 4/5] END ........C=100, gamma=1, kernel=rbf;, score=0.521 total time= 0.0s\n",
"[CV 5/5] END ........C=100, gamma=1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END ......C=100, gamma=0.1, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END ......C=100, gamma=0.1, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END ......C=100, gamma=0.1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END ......C=100, gamma=0.1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END ......C=100, gamma=0.1, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END .....C=100, gamma=0.01, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END .....C=100, gamma=0.01, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END .....C=100, gamma=0.01, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END .....C=100, gamma=0.01, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END .....C=100, gamma=0.01, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 1/5] END ....C=100, gamma=0.001, kernel=rbf;, score=0.531 total time= 0.0s\n",
"[CV 2/5] END ....C=100, gamma=0.001, kernel=rbf;, score=0.551 total time= 0.0s\n",
"[CV 3/5] END ....C=100, gamma=0.001, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 4/5] END ....C=100, gamma=0.001, kernel=rbf;, score=0.542 total time= 0.0s\n",
"[CV 5/5] END ....C=100, gamma=0.001, kernel=rbf;, score=0.542 total time= 0.0s\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"GridSearchCV(estimator=SVC(),\n",
" param_grid={'C': [0.1, 1, 10, 100], 'gamma': [1, 0.1, 0.01, 0.001],\n",
" 'kernel': ['rbf']},\n",
" verbose=4)"
]
},
"metadata": {},
"execution_count": 54
}
]
},
{
"cell_type": "code",
"source": [
"grid.best_params_"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "etYOoNkpTnRz",
"outputId": "80455eff-e30e-4123-e9a6-9b32f52f6760"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"{'C': 100, 'gamma': 1, 'kernel': 'rbf'}"
]
},
"metadata": {},
"execution_count": 55
}
]
},
{
"cell_type": "code",
"source": [
"grid.best_estimator_"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "6hsj-gcsTtzz",
"outputId": "2ebd04ce-3a8f-4a40-bd33-3cbb6712d3cc"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"SVC(C=100, gamma=1)"
]
},
"metadata": {},
"execution_count": 56
}
]
},
{
"cell_type": "code",
"source": [
"grid_predictions = grid.predict(X_test_scaled)\n",
"cm = confusion_matrix(yts, grid_predictions)\n",
"sns.heatmap(cm, annot=True)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 282
},
"id": "wySPpcfJTwZ4",
"outputId": "a21be082-a465-43f8-9ff2-8ec99b5ddfc9"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f07109f4eb0>"
]
},
"metadata": {},
"execution_count": 57
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
],
"image/png": "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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"print(classification_report(yts,grid_predictions))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "_vzPlqNwTzcI",
"outputId": "bddd3b11-0fe1-417d-c22f-40db87c0225d"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.47 0.70 0.57 27\n",
" 1 0.62 0.38 0.47 34\n",
"\n",
" accuracy 0.52 61\n",
" macro avg 0.55 0.54 0.52 61\n",
"weighted avg 0.56 0.52 0.51 61\n",
"\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"from sklearn.svm import SVC\n",
"classifier = SVC(kernel = 'rbf', random_state = 0)"
],
"metadata": {
"id": "eXN5EyJ1T2eV"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from sklearn.model_selection import cross_val_score\n",
"accuracies = cross_val_score(estimator = classifier, X = xtr, y = ytr, cv = 10)\n",
"accuracies"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "aCuaTjsKT5is",
"outputId": "1777f3c2-c27f-44b0-9718-5ad13e97c1b7"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([0.56 , 0.52 , 0.41666667, 0.5 , 0.625 ,\n",
" 0.58333333, 0.58333333, 0.5 , 0.70833333, 0.625 ])"
]
},
"metadata": {},
"execution_count": 60
}
]
},
{
"cell_type": "code",
"source": [
"print(accuracies.mean())\n",
"print(accuracies.std())"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "PgMnXXXhT-TZ",
"outputId": "44c5135a-8140-4955-a649-f094a9063023"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"0.5621666666666667\n",
"0.07799946581013659\n"
]
}
]
}
]
}