Preprocessing&Modelling (3).ipynb

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    "## World Health Organization(WHO) has estimated 12 million deaths occur worldwide.\n",
    "\n",
    "    Every year due to Heart diseases. Half the deaths in the United States and other developed countries are due to cardio vascular diseases. \n"
   ],
   "metadata": {}
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   "source": [
    "## Heart Disease Is World's No. 1 Killer\n",
    "    All over the world ,in all ages, there is a lot of people catch heart diseases without noticing. It is only been detected at a late stage.\n",
    "\n",
    "    Heart disease cases nearly doubled over the period from 271 million in 1990 to 523 million in 2019, and the number of heart disease deaths rose from 12.1 million to 18.6 million\n",
    "**`How can we reduce the Heart diseases death rate?`**\n"
   ],
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   "source": [
    "    The early prognosis of cardiovascular diseases can aid in making decisions on lifestyle changes in high risk patients and in turn reduce the complications.\n",
    "    I Aim to deploy a machine learning model that can predict whether the person may have a heart disease or not.\n",
    "\n"
   ],
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   "source": [],
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  {
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   "source": [
    "import pandas as pd\r\n",
    "import numpy as np\r\n",
    "import matplotlib.pyplot as plt\r\n",
    "import seaborn as sns\r\n",
    "\r\n",
    "from sklearn.preprocessing import LabelEncoder\r\n",
    "from sklearn.naive_bayes import GaussianNB\r\n",
    "\r\n",
    "from sklearn.neighbors import KNeighborsClassifier\r\n",
    "from sklearn.neighbors import KNeighborsRegressor\r\n",
    "\r\n",
    "from sklearn.svm import SVC\r\n",
    "from sklearn.svm import SVR\r\n",
    "\r\n",
    "from sklearn.model_selection import train_test_split\r\n",
    "from sklearn.linear_model import LogisticRegression\r\n",
    "\r\n",
    "from sklearn import metrics\r\n",
    "from sklearn.metrics import confusion_matrix,classification_report\r\n",
    "\r\n",
    "from sklearn.tree import DecisionTreeClassifier\r\n",
    "from sklearn.ensemble import RandomForestClassifier\r\n",
    "from sklearn import tree\r\n",
    "from warnings import filterwarnings\r\n",
    "filterwarnings(\"ignore\")"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "###  EDA\n"
   ],
   "metadata": {}
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   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "df = pd.read_csv('heart.csv',sep=',',encoding=\"utf-8\")\r\n",
    "df.head()"
   ],
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       "      <th></th>\n",
       "      <th>age</th>\n",
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       "   age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  slope  \\\n",
       "0   63    1   3       145   233    1        0      150      0      2.3      0   \n",
       "1   37    1   2       130   250    0        1      187      0      3.5      0   \n",
       "2   41    0   1       130   204    0        0      172      0      1.4      2   \n",
       "3   56    1   1       120   236    0        1      178      0      0.8      2   \n",
       "4   57    0   0       120   354    0        1      163      1      0.6      2   \n",
       "\n",
       "   ca  thal  target  \n",
       "0   0     1       1  \n",
       "1   0     2       1  \n",
       "2   0     2       1  \n",
       "3   0     2       1  \n",
       "4   0     2       1  "
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    "\n",
    "_____________________\n",
    "**`sex : 1 = Male , 0=Female`**\n",
    "\n",
    "_____________________\n",
    "**`cp : Chest Pain`**\n",
    "\n",
    "    Angina: Angina is caused when there is not enough oxygen-rich blood flowing to a certain part of the heart. The arteries of the heart become narrow due to fatty deposits in the artery walls. The narrowing of arteries means that blood supply to the heart is reduced, causing angina.\n",
    "    Value 1: typical angina || Value 2: atypical angina || Value 3: non-anginal pain || 4: asymptomatic\n",
    "    \n",
    "\n",
    "_____________________\n",
    "**`threstbps :Resting blood pressure`**\n",
    "\n",
    "    ( Normal pressure with no exercise )\n",
    " \n",
    " \n",
    "_____________________\n",
    "**`chol: serum cholestoral in mg/dl`**\n",
    "\n",
    "    Cholesterol means the blockage for blood supply in the blood vessels\n",
    "\n",
    "\n",
    "_____________________\n",
    "**`fbs: fasting blood sugar > 120 mg/dl`**\n",
    "\n",
    "    (1 = true; 0 = false) blood sugar taken after a long gap between a meal and the test. Typically, it's taken before any meal in the morning.\n",
    "    \n",
    "    \n",
    "_____________________\n",
    "**`restecg: resting electrocardiographic results (values 0,1,2)`**\n",
    "\n",
    "     ECG values taken while person is on rest which means no exercise and normal functioning of heart is happening\n",
    "         \n",
    "_____________________\n",
    "**`thalach: maximum heart rate achieved`**\n",
    "          \n",
    "_____________________\n",
    "**`exang: exercise induced angina`**\n",
    "\n",
    "    (1 = yes; 0 = no) is chest pain while exercising or doing any physical activity.\n",
    "\n",
    "_____________________\n",
    "**`oldpeak = ST depression induced by exercise relative to rest`**\n",
    "\n",
    "    ST Depression is the difference between value of ECG at rest and after exercise.\n",
    "    An electrocardiogram records the electrical signals in your heart. It's a common and painless test used to quickly detect heart problems and monitor your heart's health. Electrocardiograms — also called ECGs or EKGs — are often done in a doctor's office, a clinic or a hospital room. ECG machines are standard equipment in operating rooms and ambulances. Some personal devices, such as smart watches, \n",
    "     \n",
    "_____________________\n",
    "**`slope:\tthe slope of the peak exercise ST segment`**\n",
    "   \n",
    "    Value 1: upsloping — Value 2: flat — Value 3: downsloping\n",
    " \n",
    "_____________________\n",
    "**`ca:\tnumber of major vessels (0-3) colored by flourosopy`**\n",
    "\n",
    "    Fluoroscopy is an imaging technique that uses X-rays to obtain real-time moving images of the interior of an object. In its primary application of medical imaging, a fluoroscope (/ˈflʊərəskoʊp/) allows a physician to see the internal structure and function of a patient, so that the pumping action of the heart or the motion of swallowing, for example, can be watched\n",
    "\n",
    "_____________________\n",
    "**`thal:The Types of thalassemia`**\n",
    " \n",
    "    (3 = normal; 6 = fixed defect; 7 = reversable defect)"
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    "df.info()"
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      "<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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       "     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  ca  thal  target  \n",
       "0        0   0     1       1  \n",
       "1        0   0     2       1  \n",
       "2        2   0     2       1  \n",
       "3        2   0     2       1  \n",
       "4        2   0     2       1  \n",
       "..     ...  ..   ...     ...  \n",
       "298      1   0     3       0  \n",
       "299      1   0     3       0  \n",
       "300      1   2     3       0  \n",
       "301      1   1     3       0  \n",
       "302      1   1     2       0  \n",
       "\n",
       "[303 rows x 14 columns]"
      ]
     },
     "metadata": {},
     "execution_count": 4
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "source": [
    "df.shape"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "(303, 14)"
      ]
     },
     "metadata": {},
     "execution_count": 5
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "source": [
    "df.isna().sum()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "age         0\n",
       "sex         0\n",
       "cp          0\n",
       "trestbps    0\n",
       "chol        0\n",
       "fbs         0\n",
       "restecg     0\n",
       "thalach     0\n",
       "exang       0\n",
       "oldpeak     0\n",
       "slope       0\n",
       "ca          0\n",
       "thal        0\n",
       "target      0\n",
       "dtype: int64"
      ]
     },
     "metadata": {},
     "execution_count": 6
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "source": [
    "df.apply(lambda x:len(x.unique()))\r\n"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "age          41\n",
       "sex           2\n",
       "cp            4\n",
       "trestbps     49\n",
       "chol        152\n",
       "fbs           2\n",
       "restecg       3\n",
       "thalach      91\n",
       "exang         2\n",
       "oldpeak      40\n",
       "slope         3\n",
       "ca            5\n",
       "thal          4\n",
       "target        2\n",
       "dtype: int64"
      ]
     },
     "metadata": {},
     "execution_count": 7
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "source": [
    "print('cp ',df['cp'].unique())\r\n",
    "print('fbs ',df['fbs'].unique())\r\n",
    "print('restecg ',df['restecg'].unique())\r\n",
    "print('exang ',df['exang'].unique())\r\n",
    "print('slope ',df['slope'].unique())\r\n",
    "print('ca ',df['ca'].unique())\r\n",
    "print('thal ',df['thal'].unique())\r\n"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "cp  [3 2 1 0]\n",
      "fbs  [1 0]\n",
      "restecg  [0 1 2]\n",
      "exang  [0 1]\n",
      "slope  [0 2 1]\n",
      "ca  [0 2 1 3 4]\n",
      "thal  [1 2 3 0]\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "source": [
    "plt.hist(df['age'], bins=None, range=None, density=False)"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "(array([ 1., 11., 33., 38., 37., 60., 63., 43., 14.,  3.]),\n",
       " array([29. , 33.8, 38.6, 43.4, 48.2, 53. , 57.8, 62.6, 67.4, 72.2, 77. ]),\n",
       " <BarContainer object of 10 artists>)"
      ]
     },
     "metadata": {},
     "execution_count": 9
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "source": [
    "fig, ax = plt.subplots(4,2, figsize = (14,14))\r\n",
    "((ax1, ax2), (ax3, ax4), (ax5, ax6), (ax7, ax8)) = ax\r\n",
    "\r\n",
    "labels = [\"Male\", \"Female\"]\r\n",
    "values = df['sex'].value_counts().tolist()[:2]\r\n",
    "ax1.pie(x=values, labels=labels, autopct=\"%1.1f%%\",colors=['#AAb3ff','#CC80FF'],shadow=True, startangle=45,explode=[0.1, 0.1])\r\n",
    "ax1.set_title(\"Sex\", fontdict={'fontsize': 12},fontweight ='bold')\r\n",
    "\r\n",
    "labels = [\"Typical angina\", \"Atypical angina\",\"non-anginal pain\",\"asymptomatic\"]\r\n",
    "values = df['cp'].value_counts().tolist()\r\n",
    "ax2.pie(x=values, labels=labels, autopct=\"%1.1f%%\",colors=['#AAb3ff','#CC80FF','#DD00AA','#FF0099'],shadow=True,startangle=45,explode=[0.1, 0.1, 0.1, 0.2])\r\n",
    "ax2.set_title(\"Chest Pain\", fontdict={'fontsize': 12},fontweight ='bold')\r\n",
    "\r\n",
    "labels = df['fbs'].value_counts().index.tolist()[:2]\r\n",
    "values = df['fbs'].value_counts().tolist()\r\n",
    "ax3.pie(x=values, labels=labels, autopct=\"%1.1f%%\",colors=['#AAb3ff','#CC80FF'],shadow=True, startangle=45,explode=[0.1, 0.15])\r\n",
    "ax3.set_title(\"Fasting Blood Sugar\", fontdict={'fontsize': 12},fontweight ='bold')\r\n",
    "\r\n",
    "labels = df['restecg'].value_counts().index.tolist()[:3]\r\n",
    "values = df['restecg'].value_counts().tolist()\r\n",
    "ax4.pie(x=values, labels=labels, autopct=\"%1.1f%%\", colors=['#AAb3ff','#CC80FF','#DD00AA'],shadow=True,startangle=45,explode=[ 0.05, 0.05, 0.05])\r\n",
    "ax4.set_title(\"Resting Blood Pressure\", fontdict={'fontsize': 12},fontweight ='bold')\r\n",
    "\r\n",
    "labels = df['exang'].value_counts().index.tolist()[:2]\r\n",
    "values = df['exang'].value_counts().tolist()\r\n",
    "ax5.pie(x=values, labels=labels, autopct=\"%1.1f%%\", colors=['#AAb3ff','#CC80FF'],shadow=True, startangle=45,explode=[0.1, 0.1])\r\n",
    "ax5.set_title(\"Exercise induced Angina\", fontdict={'fontsize': 12},fontweight ='bold')\r\n",
    "\r\n",
    "labels = df['slope'].value_counts().index.tolist()[:3]\r\n",
    "values = df['slope'].value_counts().tolist()\r\n",
    "ax6.pie(x=values, labels=labels, autopct=\"%1.1f%%\", colors=['#AAb3ff','#CC80FF','#DD00AA'],shadow=True,startangle=45,explode=[  0.1, 0.1, 0.1])\r\n",
    "ax6.set_title(\"Peak exercise ST_segment Slope\", fontdict={'fontsize': 12},fontweight ='bold')\r\n",
    "\r\n",
    "labels = df['ca'].value_counts().index.tolist()[:5]\r\n",
    "values = df['ca'].value_counts().tolist()\r\n",
    "ax7.pie(x=values, labels=labels, autopct=\"%1.1f%%\", shadow=True, startangle=45,explode=[0.05, 0.07, 0.1, 0.1,0.1],colors=['#AAb3ff','#CC80FF','#DD00AA','#FF0099','#FF9933'])\r\n",
    "ax7.set_title(\"Major vessels\", fontdict={'fontsize': 12},fontweight ='bold')\r\n",
    "\r\n",
    "labels = df['thal'].value_counts().index.tolist()[:4]\r\n",
    "values = df['thal'].value_counts().tolist()\r\n",
    "ax8.pie(x=values, labels=labels, autopct=\"%1.1f%%\", shadow=True, startangle=45,explode=[0.1, 0.1, 0.1, 0.2],colors=['#AAb3ff','#CC80FF','#DD00AA','#FF5099'])\r\n",
    "ax8.set_title(\"Types of Thalassemia\", fontdict={'fontsize': 12},fontweight ='bold')\r\n",
    "\r\n",
    "plt.tight_layout()\r\n",
    "plt.show()\r\n",
    "\r\n",
    "plt.savefig(\"PiePlots.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1008x1008 with 8 Axes>"
      ]
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {}
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "source": [
    "df.columns"
   ],
   "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": 11
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "source": [
    "sns.catplot('target','age',data=df,kind='violin')\r\n",
    "plt.title('relationship between age and Heart Disease')\r\n",
    "plt.savefig(\"age.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "source": [
    "sns.catplot('target','thalach',data=df,kind='violin')\r\n",
    "plt.title('relationship between maximum heart rate achieved and Heart Disease')\r\n",
    "plt.savefig(\"thalach.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "source": [
    "sns.catplot('target','trestbps',data=df,kind='violin')\r\n",
    "plt.title('relationship between Resting blood pressure and Heart Disease')\r\n",
    "plt.savefig(\"trestbps.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "source": [
    "sns.catplot('target','chol',data=df,kind='violin')\r\n",
    "plt.title('relationship between Serum Cholestoral and Heart Disease')\r\n",
    "plt.savefig(\"chol.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "source": [
    "sns.catplot('target','oldpeak',data=df,kind='violin')\r\n",
    "plt.title('relationship between oldpeak and Heart Disease')\r\n",
    "plt.savefig(\"oldpeak.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "source": [
    "plt.figure(figsize=(20,10))\r\n",
    "sns.countplot(x=df['age'],data=df,hue='target',palette=\"twilight_shifted\",saturation=2,dodge=True,)\r\n",
    "\r\n",
    "plt.savefig(\"Target&age.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "source": [
    "plt.figure(figsize=(10,5))\r\n",
    "plt.scatter(x=df.age[df.target==1], y=df.thalach[(df.target==1)], c='red')\r\n",
    "plt.scatter(x=df.age[df.target==0], y=df.thalach[(df.target==0)],c='gray')\r\n",
    "plt.legend(['Positive', 'Negative'])\r\n",
    "plt.xlabel('Age')\r\n",
    "plt.ylabel('Maximum Heart Age')\r\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "source": [
    "list = ['sex','cp','fbs','restecg','exang','slope','ca','thal']\r\n",
    "m=1\r\n",
    "plt.figure(figsize=(20,15))\r\n",
    "for i in list:\r\n",
    "    plt.subplot(3,3,m)\r\n",
    "    sns.countplot(x=i,data=df,hue='target',palette=\"twilight_shifted\",\r\n",
    "    saturation=2,dodge=True)\r\n",
    "    m+=1\r\n",
    "    \r\n",
    "plt.savefig(\"TargetRelation.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x1080 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "source": [
    "plt.figure(figsize=(10,10))\r\n",
    "sns.heatmap(pd.DataFrame(df.corr()['target']).sort_values(by='target').transpose().drop('target',axis=1).transpose(),annot=True,cmap='twilight')\r\n",
    "plt.savefig(\"TargetCorrelations.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "source": [
    "X = df.drop('target',axis=1)\n",
    "Y = df['target']\n",
    "from sklearn.feature_selection import SelectKBest, chi2\n",
    "fs = SelectKBest(score_func=chi2, k='all')\n",
    "fs.fit(X, Y)\n",
    "per = []\n",
    "for i in fs.scores_:\n",
    "    per.append(round(((i/sum(fs.scores_))*100),3))\n",
    "\n",
    "features_data = pd.DataFrame({'Feature':X.columns,'Scores':fs.scores_,'Importance (%)':per}).sort_values(by=['Scores'],ascending=False)\n",
    "\n",
    "plt.figure(figsize=(9,4))\n",
    "sns.barplot( 'Importance (%)','Feature',orient='h',data=features_data,palette='twilight_shifted_r')\n",
    "insignificant = features_data.loc[features_data['Importance (%)']<0.005]['Feature'].unique()\n",
    "features_data = features_data.set_index('Feature')\n",
    "features_data\n",
    "plt.savefig(\"FeatureImportance.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 648x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "plt.subplot(1,2,1)\n",
    "sns.histplot(data=df,hue='target',x='thalach',bins=20,element='poly')\n",
    "plt.subplot(1,2,2)\n",
    "sns.histplot(data=df,hue='target',x='oldpeak',bins=20,element='poly')\n",
    "plt.savefig(\"Thalach&oldpeak_Histplot.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "plt.subplot(1,2,1)\n",
    "sns.histplot(data=df,hue='target',x='trestbps',bins=20,element='poly')\n",
    "plt.subplot(1,2,2)\n",
    "sns.histplot(data=df,hue='target',x='chol',bins=20,element='poly')\n",
    "plt.savefig(\"Resting_blood_pressure&chol_Histplot.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "sns.heatmap(df.corr(),cbar = True, annot =True,cmap='twilight_shifted_r');\n",
    "plt.savefig(\"heatmap.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "source": [
    "df.columns\n"
   ],
   "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": 25
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "source": [
    "df.info()"
   ],
   "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"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "source": [
    "df.describe()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>slope</th>\n",
       "      <th>ca</th>\n",
       "      <th>thal</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>54.366337</td>\n",
       "      <td>0.683168</td>\n",
       "      <td>0.966997</td>\n",
       "      <td>131.623762</td>\n",
       "      <td>246.264026</td>\n",
       "      <td>0.148515</td>\n",
       "      <td>0.528053</td>\n",
       "      <td>149.646865</td>\n",
       "      <td>0.326733</td>\n",
       "      <td>1.039604</td>\n",
       "      <td>1.399340</td>\n",
       "      <td>0.729373</td>\n",
       "      <td>2.313531</td>\n",
       "      <td>0.544554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>9.082101</td>\n",
       "      <td>0.466011</td>\n",
       "      <td>1.032052</td>\n",
       "      <td>17.538143</td>\n",
       "      <td>51.830751</td>\n",
       "      <td>0.356198</td>\n",
       "      <td>0.525860</td>\n",
       "      <td>22.905161</td>\n",
       "      <td>0.469794</td>\n",
       "      <td>1.161075</td>\n",
       "      <td>0.616226</td>\n",
       "      <td>1.022606</td>\n",
       "      <td>0.612277</td>\n",
       "      <td>0.498835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>126.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>47.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>211.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>133.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>55.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>153.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>61.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>140.000000</td>\n",
       "      <td>274.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>166.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>77.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>564.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>202.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.200000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              age         sex          cp    trestbps        chol         fbs  \\\n",
       "count  303.000000  303.000000  303.000000  303.000000  303.000000  303.000000   \n",
       "mean    54.366337    0.683168    0.966997  131.623762  246.264026    0.148515   \n",
       "std      9.082101    0.466011    1.032052   17.538143   51.830751    0.356198   \n",
       "min     29.000000    0.000000    0.000000   94.000000  126.000000    0.000000   \n",
       "25%     47.500000    0.000000    0.000000  120.000000  211.000000    0.000000   \n",
       "50%     55.000000    1.000000    1.000000  130.000000  240.000000    0.000000   \n",
       "75%     61.000000    1.000000    2.000000  140.000000  274.500000    0.000000   \n",
       "max     77.000000    1.000000    3.000000  200.000000  564.000000    1.000000   \n",
       "\n",
       "          restecg     thalach       exang     oldpeak       slope          ca  \\\n",
       "count  303.000000  303.000000  303.000000  303.000000  303.000000  303.000000   \n",
       "mean     0.528053  149.646865    0.326733    1.039604    1.399340    0.729373   \n",
       "std      0.525860   22.905161    0.469794    1.161075    0.616226    1.022606   \n",
       "min      0.000000   71.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "25%      0.000000  133.500000    0.000000    0.000000    1.000000    0.000000   \n",
       "50%      1.000000  153.000000    0.000000    0.800000    1.000000    0.000000   \n",
       "75%      1.000000  166.000000    1.000000    1.600000    2.000000    1.000000   \n",
       "max      2.000000  202.000000    1.000000    6.200000    2.000000    4.000000   \n",
       "\n",
       "             thal      target  \n",
       "count  303.000000  303.000000  \n",
       "mean     2.313531    0.544554  \n",
       "std      0.612277    0.498835  \n",
       "min      0.000000    0.000000  \n",
       "25%      2.000000    0.000000  \n",
       "50%      2.000000    1.000000  \n",
       "75%      3.000000    1.000000  \n",
       "max      3.000000    1.000000  "
      ]
     },
     "metadata": {},
     "execution_count": 27
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "___________________________________\n",
    "\n",
    "# Modelling\n",
    "___________________________"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from xgboost import XGBClassifier\n",
    "from sklearn.ensemble import AdaBoostClassifier\n",
    "from sklearn.ensemble import VotingClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn import tree\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.svm import SVR\n",
    "\n",
    "from sklearn import metrics\n",
    "from sklearn.metrics import confusion_matrix,classification_report\n",
    "from sklearn.metrics import f1_score,plot_roc_curve,accuracy_score,roc_curve,roc_auc_score,recall_score\n",
    "from mlxtend.plotting import plot_confusion_matrix\n",
    "\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "\n",
    "from sklearn.linear_model import RidgeCV\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.pipeline import make_pipeline, make_union\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "\n",
    "from sklearn.ensemble import AdaBoostRegressor\n",
    "from sklearn.feature_selection import SelectFwe, f_regression"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "source": [
    "X = df.drop('target',axis=1).values\n",
    "Y = df['target'].values"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "source": [
    "X.shape"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "(303, 13)"
      ]
     },
     "metadata": {},
     "execution_count": 30
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "source": [
    "Y.shape"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "(303,)"
      ]
     },
     "metadata": {},
     "execution_count": 31
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "source": [
    "# Split the dataset into training and testing.\n",
    "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2, random_state=0)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "source": [
    "print(X_train.shape)\n",
    "print(X_test.shape)\n",
    "print(Y_train.shape)\n",
    "print(Y_test.shape)"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "(242, 13)\n",
      "(61, 13)\n",
      "(242,)\n",
      "(61,)\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "------------------------\n",
    "**` 1-LogisticRegression`**\n",
    "----------------------"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "source": [
    "# Train and predict.\n",
    "LL = LogisticRegression(solver='liblinear',max_iter = 1000, random_state = 31)\n",
    "LL.fit(X_train,Y_train)\n",
    "Y_pred_lr = LL.predict(X_test) \n",
    "y_pred_lr = np.around(Y_pred_lr)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "source": [
    "score_lr = round(accuracy_score(Y_pred_lr,Y_test)*100,2)\n",
    "score_lr"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "85.25"
      ]
     },
     "metadata": {},
     "execution_count": 35
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "source": [
    "# Confusion matrix.\n",
    "conf_mat = metrics.confusion_matrix(Y_test,Y_pred_lr)\n",
    "plot_confusion_matrix(conf_mat,class_names=[\"Negative\",\"Positive\"],figsize=(12,5),cmap='copper_r'); #fn\n",
    "plt.savefig(\"LRcrr.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {
    "scrolled": true
   }
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "source": [
    "plot_roc_curve(LL,X_test,Y_test)\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('Receiver Operating Characteristic Curve');\n",
    "plt.savefig(\"LR.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "source": [
    "from sklearn import metrics\n",
    "print(metrics.classification_report(Y_test,y_pred_lr))"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.85      0.81      0.83        27\n",
      "           1       0.86      0.88      0.87        34\n",
      "\n",
      "    accuracy                           0.85        61\n",
      "   macro avg       0.85      0.85      0.85        61\n",
      "weighted avg       0.85      0.85      0.85        61\n",
      "\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "------------------------\n",
    "**`-2-  - KNN CLF`**\n",
    "----------------------"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "source": [
    "kclf = KNeighborsClassifier(n_neighbors=31,leaf_size=30)\n",
    "kclf.fit(X_train,Y_train)\n",
    "Y_pred_kclf = kclf.predict(X_test)\n",
    "score_kclf = round(accuracy_score(Y_pred_kclf,Y_test)*100,2)\n",
    "score_kclf"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "68.85"
      ]
     },
     "metadata": {},
     "execution_count": 39
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "source": [
    "conf_mat=confusion_matrix(Y_test,Y_pred_kclf)\n",
    "plot_confusion_matrix(conf_mat,class_names=[\"Negative\",\"Positive\"],figsize=(12,5),cmap='copper_r'); #fn\n",
    "plt.savefig(\"KNNcrr.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "Y_pred_kclf = np.around(Y_pred_kclf)\n",
    "print(metrics.classification_report(Y_test,Y_pred_kclf))"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "source": [
    "plot_roc_curve(kclf,X_test,Y_test)\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('Receiver Operating Characteristic Curve');\n",
    "plt.savefig(\"KNN.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "-----------------------\n",
    "**`-3-  SVM`**\n",
    "--------------------"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "source": [
    "svm = SVC(C=8.0,\n",
    "    kernel='rbf',\n",
    "    degree=3,\n",
    "    gamma='scale',\n",
    "    coef0=0.01,\n",
    "    shrinking=True,\n",
    "    probability=True,\n",
    "    tol=0.1,\n",
    "    cache_size=300,\n",
    "    class_weight=None,\n",
    "    verbose=False,\n",
    "    max_iter=-1,\n",
    "    decision_function_shape='ovo')\n",
    "svm.fit(X_train,Y_train)\n",
    "Y_pred_svm = svm.predict(X_test)         \n",
    "score_svm = round(accuracy_score(Y_pred_svm,Y_test)*100,2)\n",
    "score_svm"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "70.49"
      ]
     },
     "metadata": {},
     "execution_count": 43
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "source": [
    "conf_mat=confusion_matrix(Y_test,Y_pred_svm)\n",
    "plot_confusion_matrix(conf_mat,class_names=[\"Negative\",\"Positive\"],figsize=(12,5),cmap='copper_r'); #fn\n",
    "plt.savefig(\"SVCcrr.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "source": [
    "Y_pred_svm = np.around(Y_pred_svm)\n",
    "print(metrics.classification_report(Y_test,Y_pred_svm))"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.71      0.56      0.63        27\n",
      "           1       0.70      0.82      0.76        34\n",
      "\n",
      "    accuracy                           0.70        61\n",
      "   macro avg       0.71      0.69      0.69        61\n",
      "weighted avg       0.71      0.70      0.70        61\n",
      "\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "source": [
    "plot_roc_curve(svm,X_test,Y_test)\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('Receiver Operating Characteristic Curve');\n",
    "plt.savefig(\"SVC.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "-----------------------\n",
    "**`-4-  Navie Bayes`**\n",
    "--------------------"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "source": [
    "gnb = GaussianNB( var_smoothing=1e-50)\n",
    "gnb.fit(X_train,Y_train)\n",
    "gnb.predict(X_test)\n",
    "Y_pred_gnb = gnb.predict(X_test)          \n",
    "score_gnb = round(accuracy_score(Y_pred_gnb,Y_test)*100,2)\n",
    "score_gnb"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "85.25"
      ]
     },
     "metadata": {},
     "execution_count": 47
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "source": [
    "conf_mat=confusion_matrix(Y_test,Y_pred_gnb)\n",
    "plot_confusion_matrix(conf_mat,class_names=[\"Negative\",\"Positive\"],figsize=(12,5),cmap='copper_r'); #fn\n",
    "plt.savefig(\"GNBcrr.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "source": [
    "plot_roc_curve(gnb,X_test,Y_test)\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('Receiver Operating Characteristic Curve');\n",
    "plt.savefig(\"GNB.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "source": [
    "Y_pred_gnb = np.around(Y_pred_gnb)\n",
    "print(metrics.classification_report(Y_test,Y_pred_gnb))"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.88      0.78      0.82        27\n",
      "           1       0.84      0.91      0.87        34\n",
      "\n",
      "    accuracy                           0.85        61\n",
      "   macro avg       0.86      0.84      0.85        61\n",
      "weighted avg       0.85      0.85      0.85        61\n",
      "\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "-----------------------\n",
    "**`-5- RandomForestClassifier with GridSearch`**\n",
    "--------------------"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "source": [
    "param_grid ={\n",
    "    'max_depth': [10, 20, 30, 40,50,60,70],\n",
    " 'max_features': ['auto', 'sqrt'],\n",
    " 'n_estimators': [20, 40,60,80 ]\n",
    "}\n"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "source": [
    "RFclf = RandomForestClassifier(max_depth=10, n_estimators=20)\n",
    "grid = GridSearchCV(estimator=RFclf, param_grid=param_grid, cv = 4, n_jobs=2,verbose=2)\n",
    "grid_result = grid.fit(X_train, Y_train)\n",
    "# Summarize results\n",
    "print(\"Best: %f using %s\" % (grid_result.best_score_, grid_result.best_params_))"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Fitting 4 folds for each of 56 candidates, totalling 224 fits\n",
      "Best: 0.839003 using {'max_depth': 50, 'max_features': 'auto', 'n_estimators': 40}\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "source": [
    "model=grid_result.best_estimator_\n",
    "model"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "RandomForestClassifier(max_depth=50, n_estimators=40)"
      ]
     },
     "metadata": {},
     "execution_count": 53
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "source": [
    "Y_pred_RFclf=model.predict(X_test)\n",
    "score_RFclf = round(accuracy_score(Y_pred_RFclf,Y_test)*100,2)\n",
    "score_RFclf"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "85.25"
      ]
     },
     "metadata": {},
     "execution_count": 54
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "source": [
    "conf_mat=confusion_matrix(Y_test,Y_pred_RFclf)\n",
    "plot_confusion_matrix(conf_mat,class_names=[\"Negative\",\"Positive\"],figsize=(12,5),cmap='copper_r'); #fn\n",
    "plt.savefig(\"RF_GridSearch_crr.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "source": [
    "Y_pred_RFclf = np.around(Y_pred_RFclf)\n",
    "print(metrics.classification_report(Y_test,Y_pred_RFclf))"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.85      0.81      0.83        27\n",
      "           1       0.86      0.88      0.87        34\n",
      "\n",
      "    accuracy                           0.85        61\n",
      "   macro avg       0.85      0.85      0.85        61\n",
      "weighted avg       0.85      0.85      0.85        61\n",
      "\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "source": [
    "plot_roc_curve(model,X_test,Y_test)\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('Receiver Operating Characteristic Curve');\n",
    "plt.savefig(\"RF_GridSearch.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "-----------------------\n",
    "**`-6- RandomForestClassifier`**\n",
    "--------------------"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "source": [
    "max_accuracy = 0\n",
    "\n",
    "\n",
    "for x in range(500):\n",
    "    rf = RandomForestClassifier(random_state=x)\n",
    "    rf.fit(X_train,Y_train)\n",
    "    Y_pred_rf = rf.predict(X_test)\n",
    "    current_accuracy = round(accuracy_score(Y_pred_rf,Y_test)*100,2)\n",
    "    if(current_accuracy>max_accuracy):\n",
    "        max_accuracy = current_accuracy\n",
    "        best_x = x\n",
    "\n",
    "print(max_accuracy)\n",
    "print(best_x)\n",
    "\n"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "90.16\n",
      "323\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "source": [
    "rf = RandomForestClassifier(random_state=best_x)\n",
    "rf.fit(X_train,Y_train)\n",
    "Y_pred_rf = rf.predict(X_test)\n",
    "Y_pred_rf.shape\n"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "(61,)"
      ]
     },
     "metadata": {},
     "execution_count": 59
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "source": [
    "score_rf = round(accuracy_score(Y_pred_rf,Y_test)*100,2)\n",
    "score_rf"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "90.16"
      ]
     },
     "metadata": {},
     "execution_count": 60
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "source": [
    "conf_mat=confusion_matrix(Y_test,Y_pred_rf)\n",
    "plot_confusion_matrix(conf_mat,class_names=[\"Negative\",\"Positive\"],figsize=(12,5),cmap='cividis_r'); #fn\n",
    "plt.savefig(\"RFcrr.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "source": [
    "Y_pred_rf = np.around(Y_pred_rf)\n",
    "print(metrics.classification_report(Y_test,Y_pred_rf))"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.92      0.85      0.88        27\n",
      "           1       0.89      0.94      0.91        34\n",
      "\n",
      "    accuracy                           0.90        61\n",
      "   macro avg       0.90      0.90      0.90        61\n",
      "weighted avg       0.90      0.90      0.90        61\n",
      "\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "source": [
    "plot_roc_curve(rf,X_test,Y_test)\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('Receiver Operating Characteristic Curve');\n",
    "plt.savefig(\"RF.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "-----------------------\n",
    "**`-7- XGBoost `**\n",
    "--------------------"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "source": [
    "xgb= XGBClassifier(loss='exponential', learning_rate=0.001, n_estimators=800, subsample=1.0, criterion='friedman_mse', \n",
    "                                  min_samples_split=2, \n",
    "                                  min_samples_leaf=5, min_weight_fraction_leaf=0.2, max_depth=20, min_impurity_decrease=0.1, \n",
    "                                  min_impurity_split=None, \n",
    "                                  init=None, random_state=None, max_features=None, verbose=1, max_leaf_nodes=None, warm_start=False, \n",
    "                                  presort='deprecated', \n",
    "                                  validation_fraction=0.2, n_iter_no_change=None, tol=0.0002)\n",
    "                              \n",
    "xgb.fit(X_train, Y_train)\n",
    "Y_pred_xgb=xgb.predict(X_test)\n",
    "score_xgb = round(accuracy_score(Y_pred_xgb,Y_test)*100,2)\n",
    "score_xgb"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "[06:47:38] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:573: \n",
      "Parameters: { \"criterion\", \"loss\", \"min_impurity_decrease\", \"min_samples_leaf\", \"min_samples_split\", \"min_weight_fraction_leaf\", \"presort\", \"tol\", \"validation_fraction\", \"verbose\", \"warm_start\" } might not be used.\n",
      "\n",
      "  This may not be accurate due to some parameters are only used in language bindings but\n",
      "  passed down to XGBoost core.  Or some parameters are not used but slip through this\n",
      "  verification. Please open an issue if you find above cases.\n",
      "\n",
      "\n",
      "[06:47:38] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:1095: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "81.97"
      ]
     },
     "metadata": {},
     "execution_count": 64
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "source": [
    "conf_mat=confusion_matrix(Y_test,Y_pred_xgb)\n",
    "plot_confusion_matrix(conf_mat,class_names=[\"Negative\",\"Positive\"],figsize=(12,5),cmap='copper_r'); #fn\n",
    "plt.savefig(\"GNBcrr.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWAAAAFaCAYAAAAggIeHAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAbdUlEQVR4nO3debhdVX3/8feHJAwhYTSAzIMMIkUQqCBapCqjgAjUgVYBAbURnFCRKgK1BcU6gCAEFeUnWkFEqWARhxKxDDKDBkQZBAUrDhAGCcP398fesbcxCTfAybq59/16nvvcc/Zw9vfc597PXWftvddKVSFJWvgWa12AJI1VBrAkNWIAS1IjBrAkNWIAS1IjBrAkNTK+dQGLgqUWH1+Tl5zQugyNUGs+e7nWJWgEu+pn99xbVVPmts4AHobJS05gr63WbV2GRqjPfHCP1iVoBMv2x94xr3V2QUhSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSI+NbF6CRa/kpq/DGw49lmeVXpKq45Pyz+cHXv8QL/mYHdn3jVFZZc10+MvW1/PJnP2ldqkaAPz7wJw48/gJuvO23JOHz792FbZ63euuyRrSBBXCSAj5eVe/unx8GTKqqo57h4xxRVf865Pl/V9WLnsljjFWPP/4Y55zyUe68ZQZLLDWR959yNjOuupRf3/5zpn3o7bz+nR9qXaJGkLefeBE7/fW6fO3oVzPr0cd56JFHW5c04g2yC+IR4NVJnjXAYwAcMfSJ4fvMuf/393LnLTMAeOThh7jnjltZ7lkrcc8vb+U3d93etjiNKPc/+AjTr7+TN+3yfAAWnzCO5SYt2biqkW+QAfwYMA1455wrkkxJck6SH/df2w5ZflGSq5OcmuSO2QGe5BtJrkrykyQH98uOA5ZKcm2SM/tlD/Tfv5pklyHH/EKSvZKMS3J8f9zrk7x5gD+DUWOFlVdljec8l9tnXN+6FI1At979R6YsN5H9P3I+mx/0eQ48/gIefHhW67JGvEGfhDsJ2DfJsnMs/xTwiaraCtgL+Gy//EPA96vqBcC5wJpD9jmgqrYAtgQOTbJiVR0OPFxVm1XVvnMc49+B1wAkWRx4GXAB8Cbgvv7YWwEHJVnnGXq/o9ISS07kzUd9krNPPo4/PfRg63I0Aj32+BNc/bN7eOvum3PNaQew9JITOO4rl7Yua8Qb6Em4qro/yRnAocDDQ1a9HNg4yeznyySZDLwY2LPf9z+T/GHIPocm2bN/vAawPvC7+Rz+28AJSZYAdgKmV9XDSXYANk2yd7/dsv1r3TZ0576VfTDApCUmLMC7Hl0WGzeeg4/6JFd873yuveS7rcvRCLX6lMmsPmUZXrjxagDsvd1GHPdlA/jJLIyrID4JXA2cPmTZYsA2VTU0lMmQRJ5j+UvpQnubqnooyX8B8+1gqqo/9dvtSNcS/srslwMOqaoLn2T/aXRdKKy0zFI1v21Hs3847Bju+eWtfO9rX2xdikawVVaYxBorTebmX/6ODddcke9dfTsbrz3o0z+LvoEHcFX9PslZdB/9P98v/g7wNuB4gCSbVdW1wCXA3wEf6Vuqy/fbLwv8oQ/fjYCthxzi0SQTqmpup1z/HTiQrttiv37ZhcBbk3y/qh5NsgHwq6rys/Uc1tvkBWy9wx7cdevNHHHqOQB883OfZPyExXnNIUcwadkVmPqvJ3PXz2/mxMMPblytWjvx0B3Y91/OY9Zjj7Pus5fj9Pft2rqkES9Vg2ncJXmgqib1j1em+4j/0ao6qj+xdhLwXLp/AtOr6i1JVqJrqS4PXEzXcp3dP/sNYDXgZmAKcFRV/VeSjwC7A1dX1b5zHHcCcA9wXlXt3y9bDPgwsBtda/i3wKuq6r55vZeVllmq9tpq3WfqR6NR5jMf3KN1CRrBsv2xV1XVlnNbN7AW8OwQ7B//Bpg45Pm99CfI5nAfsGNVPZZkG2D7qnqkX7fzPI7zPuB98zjuo8CKc2z/BN2la//n8jVJWthG2p1wawJn9a3UWcBBjeuRpIEZUQFcVbcAm7euQ5IWBgfjkaRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGDGBJasQAlqRGxs9rRZKZQM1+2n+v/nFV1TIDrk2SRrV5BnBVTV6YhUjSWDOsLogkL06yf//4WUnWGWxZkjT6PWkAJ/kQ8D7g/f2ixYEvDbIoSRoLhtMC3hPYHXgQoKp+Ddg9IUlP03ACeFZVFf0JuSRLD7YkSRobhhPAZyU5FVguyUHAd4HTBluWJI1+87wKYraq+liSVwD3AxsAR1bVRQOvTJJGuScN4N4NwFJ03RA3DK4cSRo7hnMVxIHAFcCrgb2By5IcMOjCJGm0G04L+D3A5lX1O4AkKwL/DXx+kIVJ0mg3nJNwdwEzhzyfCdw5mHIkaeyY31gQ7+of/gq4PMk36fqA96DrkpAkPQ3z64KYfbPFL/qv2b45uHIkaeyY32A8Ry/MQiRprHnSk3BJpgDvBZ4HLDl7eVX97QDrkqRRbzgn4c4EbgLWAY4Gbgd+PMCaJGlMGE4Ar1hVnwMeraqLq+oAYOsB1yVJo95wrgN+tP9+d5JdgV8Dqw+uJEkaG4YTwB9OsizwbuBEYBngnQOtSpLGgOEMxvOt/uF9wPaDLUeSxo753YhxIv87KedfqKpDB1KRJI0R82sBX7nQqhjh1lxteT7zL3u3LkMjVLY5pnUJWkTN70aMLy7MQiRprBnWrMiSpGeeASxJjRjAktTIcGbE2CDJ95Lc2D/fNMkHBl+aJI1uw2kBnwa8n/6OuKq6HnjtIIuSpLFgOAE8sarmHID9sUEUI0ljyXAC+N4k69HflJFkb+DugVYlSWPAcMaCmApMAzZK8ivgNuDvB1qVJI0BwxkL4lbg5UmWBharqplPto8k6ckNZ0aMI+d4DkBVef+lJD0Nw+mCeHDI4yWBVwIzBlOOJI0dw+mC+Lehz5N8DDhvYBVJ0hjxVO6Emwis+0wXIkljzXD6gG/gf8cFHgdMAez/laSnaTh9wK8c8vgx4DdV5Y0YkvQ0zTeAkywGnF9VmyykeiRpzJhvH3BVPQFcl2TNhVSPJI0Zw+mCeDbwkyRXMOSStKrafWBVSdIYMJwAPnrgVUjSGDScAN6lqt43dEGSjwAXD6YkSRobhnMd8CvmsmznZ7oQSRpr5tkCTvJW4B+BdZNcP2TVZOBHgy5Mkka7+XVBfBn4NnAscPiQ5TOr6vcDrUqSxoB5BnBV3QfcB7xu4ZUjSWOHsyJLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiMGsCQ1YgBLUiPjWxegRcvae36KyROXYNy4MH7cYlx5+kGtS1Ijq6++OmeccQarrLIKTzzxBNOmTeOEE05g00035ZRTTmHSpEncfvvt7LvvvsycObN1uSNSkwBO8jhwQ3/8GcAbq+qhBdh/VeCEqto7yWbAqlV1Qb9ud2Djqjruma9cAD846Q08a7mJrctQY4899hjvfve7ueaaa5g0aRJXXXUVF110EZ/97Gc57LDDmD59Ovvvvz/vec97OPLII1uXOyK16oJ4uKo2q6pNgFnAWxZk56r6dVXt3T/dDNhlyLrzDF9p8O655x6uueYaAB544AFmzJjBaqutxoYbbsj06dMBuOiii9hrr71aljmijYQ+4B8Cz0myQpJvJLk+yWVJNgVIsl2Sa/uva5JMTrJ2khuTLA4cA7ymX/+aJPsl+XSSZZPcnmSx/nUmJrkzyYQk6yX5zyRXJflhko0avv9FShJ2ePuX2GK/05j2jatal6MRYq211mLzzTfn8ssv58Ybb2T33XcHYJ999mGNNdZoXN3I1TSAk4wHdqbrjjgauKaqNgWOAM7oNzsMmFpVmwEvAR6evX9VzQKOBL7at6i/OmTdfcB1wHb9ot2AC6vqUWAacEhVbdG//skDe5OjzI9O3Z+rv3gw3/746znpnCuZfs0drUtSY0svvTTnnHMO73jHO5g5cyYHHHAAU6dO5corr2Ty5MnMmjWrdYkjVquTcEslubZ//EPgc8DlwF4AVfX9JCsmWRb4EfDxJGcCX6+qu5IM9zhfBV4D/AB4LXBykknAi4Czh7zOEnPumORg4GCANVdZdoHf4Gi16pTJAKy0wtLsud2GXPHTX/E3m6/VuCq1Mn78eM455xzOPPNMzj33XABuvvlmdtxxRwDWX399dt1115Yljmit+4A3q6pD+pbs3FK1+v7cA4GlgMsWsLvgPGDnJCsAWwDfp3vPfxxy/M2q6rlzOfC0qtqyqrac4gknAB58eBYzH3zkz4+/c/mtbLLuSo2rUkuf+9znmDFjBp/4xCf+vGzKlClA1131gQ98gFNOOaVVeSPeSLoMbTqwL/DPSV4K3FtV9ydZr6puAG5Isg2wEXDtkP1mApPn9oJV9UCSK4BPAd+qqseB+5PclmSfqjo7XTN406q6bmDvbJT4ze8fZM/DzwLgscef4PU7bMJO2zyncVVqZdttt+UNb3gD119//Z9Pxh1xxBGsv/76TJ06FYCvf/3rnH766S3LHNFSVQv/oMkDVTVpjmUrAKcD6wAPAQdX1fVJTgS2Bx4HfgrsBzybLlA36fe7EJgAHEvXUt6yqt7Wv+7ewNnAS6vq4n7ZOsBn+teZAPx7VR0zr3q3fO6q5fWumpdsM89fHQngqqracm4rmgTwosYA1vwYwHoS8wzgkXAZmiSNSQawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSIwawJDViAEtSI6mq1jWMeEl+C9zRuo4R5FnAva2L0Ijl78f/tVZVTZnbCgNYCyzJlVW1Zes6NDL5+zF8dkFIUiMGsCQ1YgDrqZjWugCNaP5+DJN9wJLUiC1gSWrEAJakRgxgSWrEAJa00CRJ6xpGEgNYAzP7jy3Js5Os2roetZUk1Z/1T/LcJGuM9UD2KggNVJJXAe8A7gNuAk6sqrta1qS2krwN+DvgWmAT4GU1RoPIFrAGJslfAe8CXglcAWxPF8Qao5LsCOwJ7ArcDzzWtqK2DGAN0uPAt4B96P7gXltVM5M8r21ZauiPdDdqHAj8NfDKqqokOzStqpHxrQvQ6JNkY2Bjuo+YLwFWAV5XVbcm2Rn4YJJXV9U9DcvUQpRkf2AC8D3gAuDWqtqqX7cfsEuSy6tqTH1CsgWsQdgWeGdV/ZzuD+4W4KVJXg98DPhXw3d0SzJnttwG7A78CngrsGqSfZP8E3AocMxYC1/wJJyeAbPPbicZV1WP98u+DFxaVScmORBYC1gB+GZVfWfoGXGNfklWBI4Bzqqqi5PsDbwQKODzVXVT0wIbMYD1lCXZAHh+VZ2dZEtgO+AXVfWNJC8Hdqiq9w7ZfkJVPdqqXg1e37+/RVWdkeSVdK3ddwG3AnsB/wRsXVUPNixzxLALQk/HYsD/JJkM3AksAUxN8mngUbp+vX8Ysv2YPuM92vXdDisCFyRZB/gBcCNwCHAGcBVwMbBTsyJHGFvAelqSjKebfuZ9VXVqkqWAjwO30/3h3QS8qqoeaFelBi3J4lU1q3+8OnA0cF1VnZBkeeANwGuANYFL6E7KjvnwMYC1QJJMBF5RVd9M8kJgFhDgP4F/qapP9S2hVeguP/t5VZ3frmINWpJl6U68TgdeRHe1w+LAy+hOvn2yqh7vr455Pl0w/7RVvSOJAawFluQLwJbAn4CDquqaJC8Avgt8oKpOnmN7T7iNUv0noHHAfnSt3BWB5/YnZXcDdqSb0PYTVWUX1BzsA9awDblv/1i6Kxoeq6prAKrqauDlwKeSvH3ofobv6JRkI+DkqnqE7q62LYBL6UIY4CK6a343At7WpMgRzhawhmXIpWaLAZOA5YHPA49W1U5DtlsfWLuqLmpUqhaSJOPofg+eA8wAng3sAaxOF8wzkmwIbAhcVlX/06zYEcoA1pMaEr47AFsD91TVtH7d94EHgQ8DHwX2rKrf2+0weiVZrKqeGPL8NLo7H3cBlgHe3H+/D5hCd4J2zN1kMRx2QehJ9eG7E/AJ4IfAMUlOSrJCVf0t8ADdWe9/q6rfz96nXcUalP4f6xP94x37PuC30F3ZcC4wEzgJ+AXwYuAkw3febAFrvvouh8nAF4EPAisDx9PdUvpH4JCq+kOS5arqj7Z8x4YkU+kuM9ylH+NjMbpPQJvRDbp0b5Ilq+pPLesc6QxgzdWQboeJVfVQfyvpCnRB/BJgInA38Gng6Kp6uGG5WoiSvAT4FLBTVf1Pfxfk3XT/kI8D1gN2A57wn/H8ORqa/sKQ8H0hcHKS/arqhiQr0V33uzxdGF8InGP4jm5z+VTzKN1dbvv2M53sCtwFvLeqDkmy8uwxQTR/9gHrL/Th+wq6azvHARcm+auqmkE3sPqZwH8Ap1TVj9tVqkGbYxqh1ZM8i+534BFgA+C8qtqY7s7HLQGq6jeNyl3k2AWhv9Dfx38BsH9VXZbkSLow3pXu5MqWdNcAX9GuSg3SnK3eJIcCr6e74uXnwNTZN1Yk2ZPu/MA+VfWLFvUuqmwBa25+B1xJ16qhqo4BfkTX5bByVf234Tvq/bl7su/z3Q94NV3f7hp0n4Lor455G/BGw3fBGcAaOnvxskmWrar76a58ePWQzb5A18/3zSSTFn6VWlj67qczkhzeDyv6W+Ay4O6qeqiqdgHWSrIX3ehmr6uqGxqWvMjyJJxm9/nuRjdu6x+SXAa8H/hKP7LVQ3QTa76J7tKjpemu/dUo07dojwH+H7ASXbfD1XS3E28KXNdv+n26X52HAU/CPkUG8Bg1x8mVrYEj6EYv+3u6AXY+muTv6MZ3WJNuEsWV6Ua7emLur6pFWZIV6Pr+96iq/0iyJt21vdfS/ROeluRMuk9Hu9F9KtLTYACPQUmmAK9K8pV+nN7F6QbY2YbuXv7ZM9TOmj2yWZIX0c1m+6qq+m2DsjVg/S3kuwEfTXJxVf0ySdGNbnZakvvpxnlYhe6E28+aFjwKGMBj07Z083Et0Q8tOY4ugH8H7Nzf0fYK4C1J3tIvvwN4WVXd0ahmLQRVdX6SJ4CrklxIN8vJl/t1X2ta3CjkZWhjSPpJM/tRrF4FvBT4aVV9Jsk/051025uur+9IugvrHUx9DOpPvn0HWKW/220pb7h55hnAY0Q/LOCBdH9U06vqkSQ7AzvThfApSY6iG1JwObqZai90bIexq//9+BiwvUNJDoYBPEYk2Y7u9tFbgLOAdekG1XkFXR/wr4Ev9FdEOIiKAEiyB/Ahuptvyn/GzywDeAxJ8mLgW3T9v3vRjemwJ931vc8BjqIbZJ2h471qbEsyqZxUdSA8CTeGVNUlSV4HfA14UVXNTPIt4K+Ag4HbDF7NyfAdHFvAY1CSXYATga1mD6A+ZAQ0+3ylhcQW8BhUVRf0lxrdlGTDqvrD7NA1fKWFxxbwGJZkV+DBqvqv1rVIY5EBrLkNuC1pITCAJakRh6OUpEYMYElqxACWpEYMYI1pSV7a34xCkt2THD6fbZdL8o9P4RhHJTlsuMvn2OYLSfZegGOtneTGBa1RbRjAGpX6Ed8WSFWdV1XHzWeT5YAFDmBpXgxgLVL6Ft5NSb6Y5PokX0sysV93e5Ijk1wC7JNkhySXJrk6ydmz57JLslP/GpcwZN67JPsl+XT/eOUk5ya5rv96EXAcsF6Sa5Mc32/3niQ/7ms5eshr/VOSm5N8F9hwGO/roP51rktyzuz31Ht5kh8m+VmSV/bbj0ty/JBjv/np/my18BnAWhRtCEyrqk2B+/m/rdI/VdWLge8CHwBeXlUvoJvl+V1JlgROo5tS5yV0szvMzQnAxVX1fOAFwE+Aw4FfVNVmVfWeJDsA6wN/DWwGbJHkb5JsAbwW2Jwu4Lcaxnv6elVt1R9vBt38e7OtDWwH7Aqc0r+HNwH3VdVW/esflGSdYRxHI4i3ImtRdGdV/ah//CXgULpxawG+2n/fGtgY+FG6SZ8XBy6lm1zytqq6BSDJl+gGIprT3wJvAKiqx4H7kiw/xzY79F/X9M8n0QXyZODcqnqoP8Z5w3hPmyT5MF03xyTgwiHrzuoHSbolya39e9gB2HRI//Cy/bGdJmgRYgBrUTTn3UNDnz/Yfw9wUVW9buiGSTaby/5PVYBjq+rUOY7xjqdwjC/Qzbd3XZL96GYrmW1u7zfAIVU1NKhJsvYCHlcN2QWhRdGaSbbpH78OuGQu21wGbJvkOQBJJibZALgJWCfJekP2n5vvAW/t9x2XZBlgJl3rdrYLgQOG9C2vlmQlYDqwZ5KlksyeQfjJTAbuTjIB2HeOdfskWayveV3g5v7Yb+23J8kGSZYexnE0ghjAWhTNAN6Y5HpgBeAzc27Qz9y8H/CVfrvLgI36mT4OBs7vT8LNa5LRtwPbJ7kBuAp4XlX9jq5L48Ykx1fVd+gmrLy03+5rwOSqupquK+Ra4Bzgh8N4Tx8ELgcuovsnMdTNwMXAt4G39O/hs8BPgav7y85OxU+0ixzHgtAipf+I/a2q2qR1LdLTZQtYkhqxBSxJjdgClqRGDGBJasQAlqRGDGBJasQAlqRGDGBJauT/A+oTNipg6ORcAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "source": [
    "Y_pred_gnb = np.around(Y_pred_gnb)\n",
    "print(metrics.classification_report(Y_test,Y_pred_xgb))"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.81      0.78      0.79        27\n",
      "           1       0.83      0.85      0.84        34\n",
      "\n",
      "    accuracy                           0.82        61\n",
      "   macro avg       0.82      0.82      0.82        61\n",
      "weighted avg       0.82      0.82      0.82        61\n",
      "\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "source": [
    "plot_roc_curve(gnb,X_test,Y_test)\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('Receiver Operating Characteristic Curve');\n",
    "plt.savefig(\"GNB.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "-----------------------\n",
    "**`-8- Decision Tree Classifier `**\n",
    "--------------------"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "source": [
    "tclf = DecisionTreeClassifier(\n",
    "    max_depth=20,\n",
    "    min_samples_split=2,\n",
    "    min_samples_leaf=1,\n",
    "    min_weight_fraction_leaf=0.00001,\n",
    "    max_features='auto',\n",
    "    random_state=46)\n",
    "tclf.fit(X_train, Y_train)\n",
    "Y_pred_tclf=tclf.predict(X_test)\n",
    "score_tclf = round(accuracy_score(Y_pred_tclf,Y_test)*100,2)\n",
    "score_tclf"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "83.61"
      ]
     },
     "metadata": {},
     "execution_count": 68
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "source": [
    "conf_mat=confusion_matrix(Y_test,Y_pred_tclf)\n",
    "plot_confusion_matrix(conf_mat,class_names=[\"Negative\",\"Positive\"],figsize=(12,5),cmap='copper_r'); #fn"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "source": [
    "Y_pred_tclf = np.around(Y_pred_tclf)\n",
    "print(metrics.classification_report(Y_test,Y_pred_tclf))"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.79      0.85      0.82        27\n",
      "           1       0.88      0.82      0.85        34\n",
      "\n",
      "    accuracy                           0.84        61\n",
      "   macro avg       0.83      0.84      0.83        61\n",
      "weighted avg       0.84      0.84      0.84        61\n",
      "\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "source": [
    "plot_roc_curve(tclf,X_test,Y_test)\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('Receiver Operating Characteristic Curve');"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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3vjv7nXurm5VPine6Ww7KTGbqMK/ulhnJDOiTSHysHdVHKksExnRjB+rc7pZlzZtvGsfCqThQ36z8Eb2d7pYnHZXZdEQ/0P2dkWzdLbsrSwTGRLg97pj1jUMZex/d++tu2TgUwgmDm/etz7bullHLEoExYa6+Qdle7g6N4DPg2ZaySvZUNe9umZEcT05GEuNz0/iu292y8Q7avik9rbulacESgTFhYH9NXdOR/Namo/sqtpRWsK28qkV3y+y0RHIykhkzMLXpTtnG4Yx79bR/a9Mx9o0xpgs0NCi79jV2t6xofnRfWklpRfPulr0TYsnNSGZ0/1RmHNPPOaJ3+9Zbd0vT2SwRGNNJqmvrmyYj2exzE9VWn+6WPQT6pTpj1p8+yqu7pXtkn5pkN1GZrmOJwJgAqSqlFQcONt/4jIXz9d7mY9Ynx8cwMD2JIVnJnDI8ixx3ysHc9CT6W3dLE0YsERjj5UBdA9vKq5qab7yP7v11tzyydwI56UlMHprVrLtlTrp1tzSRwxKBiTrllQda7OAb/96xp3l3y55e3S0bhzJu3OFnpyWREGfdLU3ks0Rgup26+gZ27KluNtVgU0+c0kr2Vjcfsz6zlzO65fF5aeSkDzjYhJORRFYv625puj9LBCYi7a+pc/vRV7S4OLttdxV1Xof1cTFCdppzJH/cwLSmbpaNR/fJ1t3SRDn7DzBhqaFB+XpfdbPZp7x39mU+3S1TE+PIzUji6AGpnO12t8xpGt0ykRg7qjemVZYITMhU19a3mGqwcb7ZrburOODT3bJ/H6e75Zmjj2i6gSrXnYnKulsac+gsEZigUVVK9h9oar7ZUlrF5rKKpqP7XftadrfMyUhmaN8UTh15RFPTTY47mXic3URlTFBYIjCHpaaunm27q5qO6L2P7reUVVLp092yX2oCA9OTmDosq0Vbfbp1tzQmJCwRmDapKnuqapvfKVta6R7ZV7F9TxXq1d0yIa55d8vcpp19Mtlpidbd0pgwZInANHW3bNzZezffbCmrZF+L7pY9yc1IYsKg9GYTieemJ5GV0tOO6o2JMJYIosS+6tpmQxd798TZVl5FvU93y4Fpzh2y43PTDrbVu804SfH2tTGmO7H/6G6ioUHZube6xc6+8c5Z3+6WfZLiyE1P4tjsVL45pt/BoYwzkjiyd4J1tzQmilgiiCBVB+q97pb1GgunrJLisioO1B/sbhnTQ+jfJ4Hc9GTOHH1k0yxUOe5QxqmJ1t3SGOOwRBDG9lXX8svXP2f9rv1sLqvE49PdslfPWHLSkxh+RAqnjzyiaW7ZHHd0S+tuaYwJhCWCMPbm2p08t2Ir+blpTBuW5TWRuHMzVVpSnF2YNcYcNksEYayg0ENmr5784+pJNvCZMSZogtp2ICLTReRLEVkvIrf6WZ4qIv8SkU9E5DMRuSKY8USS+gblg/UlTBmaaUnAGBNUQUsEIhIDPA7MAEYBF4nIKJ9i1wLrVHUMMA34PxGJD1ZMkWTttj2UV9YyZVhWqEMxxnRzwTwjmACsV9UNqnoAeA6Y6VNGgRRxGrp7AWVAHYaCQg8AJw/NDHEkxpjuLpiJYACw1etxsfuct8eAkcB24FPgJ6ra4FMGEblKRFaKyEqPxxOseMNKQZGHowf0JrNXz1CHYozp5oKZCPw1bKvP4zOB1UB/YCzwmIj0bvEi1Tmqmq+q+VlZ3b+pZG91LR9vKWfK0O5fV2NM6AUzERQDA70eZ+Mc+Xu7AnhJHeuBjcCIIMYUEZauL6W+Qe36gDGmSwQzEawAhorIIPcC8IXAqz5ltgCnAojIEcBwYEMQY4oIBUUekuNjGJeTFupQjDFRIGj3EahqnYhcB7wNxABzVfUzEZnlLn8SuA+YJyKf4jQl/VxVS4IVUyRQVQoKPUwakkl8rN0ZbIwJvqDeUKaqbwBv+Dz3pNff24EzghlDpNlYUkHx7iqunjI41KEYY6KEHXKGmcZuo5PtQrExpotYIggzBUUl5KQnkZeZHOpQjDFRwhJBGKmpq+fDr0qZMsxuIjPGdB1LBGFk1ebdVNXW2/0DxpguZYkgjBQUlhDbQ5g0JCPUoRhjooglgjBSUOhhXG4aKQk2e5gxputYIggTnn01rNuxl6l2N7ExpotZIggTi4ucbqN2fcAY09UsEYSJgkIPGcnxjO7fYsw9Y4wJKksEYaChQVlcVMLJNhuZMSYEAk4EImJ3OAXJuh17Ka04YM1CxpiQaDcRiMiJIrIO+Nx9PEZE/hD0yKLIoqZhJexGMmNM1wvkjOBhnAlkSgFU9RNgSjCDijYFhR5GHJlC394JoQ7FGBOFAmoaUtWtPk/VByGWqLS/po6Pt+y2bqPGmJAJZBjqrSJyIqDuBDM34DYTmcO37KtSauttNjJjTOgEckYwC7gWZ+L5Ypy5hX8cxJiiSkGRh8S4GPLzbDYyY0xoBHJGMFxVf+D9hIicBCwJTkjRpaDQwwmD0+kZGxPqUIwxUSqQM4LfB/ic6aAtpZVsKq20ZiFjTEi1ekYgIpOAE4EsEfmp16LeOHMQm8O0qHFYCUsExpgQaqtpKB7o5ZZJ8Xp+L3BeMIOKFgWFHgb0SWSwzUZmjAmhVhOBqi4CFonIPFXd3IUxRYXa+gY+/KqUb47pj4gNK2GMCZ1ALhZXishvgdFA0x1PqvqNoEUVBT7evJv9NXVMtWkpjTEhFsjF4meBL4BBwD3AJmBFEGOKCgVFHmJ6CJOGWCIwxoRWIIkgQ1X/DNSq6iJV/SFwQpDj6vYWF5UwdmAfUhNtNjJjTGgFkghq3d87RORsETkOyA5iTN1eWcUBPt22x0YbNcaEhUCuEdwvIqnATTj3D/QGbgxmUN3d4iIPqjDFrg8YY8JAu4lAVV9z/9wDnAJNdxabQ1RQWEKfpDiOze4T6lCMMabNG8pigPNxxhh6S1XXisg5wC+AROC4rgmxe1FVFhd5OOmoTGJsNjJjTBho64zgz8BAYDnwOxHZDEwCblXVBV0QW7f0xc597NpXw1S7PmCMCRNtJYJ84FhVbRCRBKAEOEpVd3ZNaN1TQeNsZHZ9wBgTJtrqNXRAVRsAVLUaKOxoEhCR6SLypYisF5FbWykzTURWi8hnIrKoI+uPRAVFHoYd0Yt+qYmhDsUYY4C2zwhGiMga928BhriPBVBVPbatFbvXGB4HTseZx2CFiLyqquu8yvQB/gBMV9UtItL30KsS/ioP1LFi424unZQb6lCMMaZJW4lg5GGuewKwXlU3AIjIc8BMYJ1Xme8DL6nqFgBV3XWY2wxrH20o40B9g402aowJK20NOne4A80NALznOi4GJvqUGQbEichCnBFOH1XVp31XJCJXAVcB5OTkHGZYobOo0EPP2B5MGJQe6lCMMaZJQJPXHyJ/fSPV53EsMB44GzgTuENEhrV4keocVc1X1fysrMg9ml5c5GHCoHQS4mw6B2NM+AhmIijG6X7aKBvY7qfMW6paoaolQAEwJogxhcy28iq+8lQw1ZqFjDFhJqBEICKJIjK8g+teAQwVkUEiEg9cCLzqU+YVYLKIxIpIEk7T0ecd3E5EaOw2atcHjDHhpt1EICLfBFYDb7mPx4qI7w69BVWtA64D3sbZuf9DVT8TkVkiMsst87m73jU4N649paprD7EuYa2g0MORvRMY2rdXqEMxxphmAhl07m6cHkALAVR1tYjkBbJyVX0DeMPnuSd9Hv8W+G0g64tUdfUNfLC+hBlHH2mzkRljwk4gTUN1qron6JF0Y58Ul7Ovus6ahYwxYSmQM4K1IvJ9IEZEhgI3AEuDG1b3sqiwhB4CJx9lw0oYY8JPIGcE1+PMV1wD/B1nOOobgxhTt1NQ6OHY7D70SYoPdSjGGNNCIGcEw1X1duD2YAfTHZVXHmBNcTnXfWNoqEMxxhi/AjkjeEhEvhCR+0RkdNAj6mY+WF9Cg8JUG23UGBOm2k0EqnoKMA3wAHNE5FMR+d9gB9ZdFBR6SEmIZYzNRmaMCVMB3VCmqjtV9XfALJx7Cu4MZlDdhTMbWQknDckkNiaYN3EbY8yhC+SGspEicreIrAUew+kxlB30yLqB9bv2s2NPtXUbNcaEtUAuFv8FmA+coaq+YwWZNixqGlbCrg8YY8JXu4lAVU/oikC6o4KiEgZnJZOdlhTqUIwxplWtJgIR+Yeqni8in9J8+OiAZiiLdtW19Xy0oZSLJkTu/AnGmOjQ1hnBT9zf53RFIN3N8o1l1NQ12LDTxpiw1+rFYlXd4f75Y1Xd7P0D/LhrwotcBYUe4mN6MHGwzUZmjAlvgfRpPN3PczM6O5DupqDIw/GD0kiKD+R6vDHGhE5b1wiuwTnyHywia7wWpQBLgh1YJNuxp4rCr/dz7jjrZWuMCX9tHa7+HXgT+BVwq9fz+1S1LKhRRbjFhSWAzUZmjIkMbSUCVdVNInKt7wIRSbdk0LqCIg9ZKT0ZcWRKqEMxxph2tXdGcA6wCqf7qPfUWgoMDmJcEau+QflgfQnfGNHXZiMzxkSEVhOBqp7j/h7UdeFEvk+37aG8sta6jRpjIkYgYw2dJCLJ7t8Xi8hDImJ3SbWioNCD2GxkxpgIEkj30SeAShEZA/wM2Aw8E9SoIlhBoYej+6eS0atnqEMxxpiABDp5vQIzgUdV9VGcLqTGx97qWv67tdwGmTPGRJRA7nbaJyK3AZcAk0UkBogLbliRaen6EuoblClD7fqAMSZyBHJGcAHOxPU/VNWdwADgt0GNKkItKiyhV89YxuWmhToUY4wJWCBTVe4EngVSReQcoFpVnw56ZBFGVSko9DBpSAZxNhuZMSaCBNJr6HxgOfA94HzgIxE5L9iBRZoNJRVsK6+yu4mNMREnkGsEtwPHq+ouABHJAt4FXghmYJGmwJ2NbKpdHzDGRJhA2jB6NCYBV2mAr4sqi4tKyMtIIifDZiMzxkSWQM4I3hKRt3HmLQbn4vEbwQsp8tTU1fPhV6V8L99GGzXGRJ5A5iy+RUS+C5yMM97QHFV9OeiRRZBVm3ZTVVvPZGsWMsZEoLbmIxgKzAaGAJ8CN6vqtq4KLJIsKvIQ20OYNCQj1KEYY0yHtdXWPxd4DTgXZwTS33d05SIyXUS+FJH1InJrG+WOF5H6SO2NVFBYwvjcNHr1tNnIjDGRp61EkKKqf1LVL1V1NpDXkRW7dyA/jjOt5SjgIhEZ1Uq5XwNvd2T94WLXvmo+37HXuo0aYyJWW4ewCSJyHAfnIUj0fqyqH7ez7gnAelXdACAiz+GMV7TOp9z1wIvA8R2MPSw0zkZmw04bYyJVW4lgB/CQ1+OdXo8V+EY76x4AbPV6XAxM9C4gIgOA77jrajURiMhVwFUAOTnhNQJ2QZGHjOR4RvXrHepQjDHmkLQ1Mc0ph7luf9Nzqc/jR4Cfq2p9W7N5qeocYA5Afn6+7zpCpqFBWVxUwpShmfToYbORGWMiUzCvbhYDA70eZwPbfcrkA8+5SSATOEtE6lR1QRDj6jSfbd9LWcUBuz5gjIlowUwEK4ChIjII2AZcCHzfu4D3NJgiMg94LVKSADjNQoDdP2CMiWhBSwSqWici1+H0BooB5qrqZyIyy13+ZLC23VUKCj2M6tebrBSbjcwYE7naTQTitNv8ABisqve68xUfqarL23utqr6Bz3AUrSUAVb08oIjDxP6aOlZt3s2VkweHOhRjjDksgQwe9wdgEnCR+3gfzv0BUe3Dr0qpa1CmDLVpKY0xkS2QpqGJqjpORP4LoKq7RSQ+yHGFvYJCD4lxMYzPs9nIjDGRLZAzglr37l+FpvkIGoIaVQQoKHJmI+sZGxPqUIwx5rAEkgh+B7wM9BWRXwIfAA8ENaowt7m0gs2lldYsZIzpFgIZhvpZEVkFnIpzk9i3VfXzoEcWxhpnI7P7B4wx3UEgvYZygErgX97PqeqWYAYWzhYVlpCdlsigzORQh2KMMYctkIvFr+NcHxAgARgEfAmMDmJcYetAXQMfflXCzOMG0NawGMYYEykCaRo6xvuxiIwDrg5aRGHu4y27qThQzxS7m9gY0010eBJ6d/jpiBwyujMsLvIQ00M48SibjcwY0z0Eco3gp14PewDjAE/QIgpzBYUljMvpQ++EuFCHYowxnSKQM4IUr5+eONcMZgYzqHBVur+Gtdv3WLOQMaZbafOMwL2RrJeq3tJF8YS1D9aXoAqTrduoMaYbafWMQERiVbUepynIAIsKPfRJiuOYAamhDsUYYzpNW2cEy3GSwGoReRX4J1DRuFBVXwpybGFF1ZmN7OSjMomx2ciMMd1IIPcRpAOlOPMKN95PoEBUJYLPd+zDs6/G7iY2xnQ7bSWCvm6PobUcTACNwmbe4K7SOBuZXSg2xnQ3bSWCGKAXgU1C3+0VFHoYfkQKR6YmhDoUY4zpVG0lgh2qem+XRRLGKg/UsXLTbi47MTfUoRhjTKdr6z4CuyLqWrahlAP1DXZ9wBjTLbWVCE7tsijCXEFhCQlxPTg+Lz3UoRhjTKdrNRGoallXBhLOCoo8TByUQUKczUZmjOl+OjzoXLQp3l3JBk+FNQsZY7otSwTtKCgsAbBpKY0x3ZYlgnYUFHrol5rAUX17hToUY4wJCksEbairb2DJVyVMGZpls5EZY7otSwRtWL21nH3VdXZ9wBjTrVkiaENBoYceAicfZdcHjDHdlyWCNiwqKmHMwD6kJtlsZMaY7ssSQSt2VxxgTXG5DTJnjOn2LBG0onE2Mrs+YIzp7oKaCERkuoh8KSLrReRWP8t/ICJr3J+lIjImmPF0xOIiD70TYhmTbbORGWO6t6AlAne+48eBGcAo4CIRGeVTbCMwVVWPBe4D5gQrno5QVQoKSzh5aCaxMXbSZIzp3oK5l5sArFfVDap6AHgOmOldQFWXqupu9+EyIDuI8QSsaNd+du6ttusDxpioEMxEMADY6vW42H2uNT8C3vS3QESuEpGVIrLS4/F0Yoj+FRQ625hs1weMMVEgmIkg4JnNROQUnETwc3/LVXWOquaran5WVvB3zosKPQzJSmZAn8Sgb8sYY0ItmImgGBjo9Tgb2O5bSESOBZ4CZqpqaRDjCUh1bT3LN5ZZbyFjTNQIZiJYAQwVkUEiEg9cCLzqXUBEcoCXgEtUtTCIsQTso41l1NTZbGTGmOjR1pzFh0VV60TkOuBtIAaYq6qficgsd/mTwJ1ABvAHd1C3OlXND1ZMgSgo9BAf24MTBmWEMgxjjOkyQUsEAKr6BvCGz3NPev19JXBlMGPoqIJCDxPy0kmMt9nIjDHRwTrJe9leXkXRrv1MGWaDzBljooclAi8fFLmzkdn1AWNMFLFE4GVRkYcjevdk+BEpoQ7FGGO6jCUCV32D8kFRCZNtNjJjTJSxROBaU1zOnqpaaxYyxkQdSwSugsISxGYjM8ZEIUsEroIiD8cMSCU9OT7UoRhjTJeyRADsqapl9VabjcwYE50sEQBL15dQ36B2fcAYE5UsEeA0C/XqGctxOX1CHYoxxnS5qE8EjbORnTgkgzibjcwYE4Wifs/3laeCbeVV1ixkjIlaUZ8IFhc5s5FNtURgjIlSUZ8ICgo9DMpMZmB6UqhDMcaYkIjqRFBTV8+yDWVMGWo3kRljoldUJ4KVm3ZTVVtv1weMMVEtqhNBQaGHuBjhhME2G5kxJnpFdSJYVOhhfG4ayT2DOlGbMcaEtahNBLv2VvPFzn3WLGSMiXpRmwgKGmcjs/GFjDFRLnoTQaGHzF7xjOrXO9ShGGNMSEVl43hDg/LB+hKmDsuiRw+bjSyUamtrKS4uprq6OtShGNMtJCQkkJ2dTVxcXMCvicpEsHb7HsoqDjBlmN0/EGrFxcWkpKSQl5dnU4Qac5hUldLSUoqLixk0aFDAr4vKpqHF7vWByXZ9IOSqq6vJyMiwJGBMJxARMjIyOnyGHZWJYFGhh9H9e5PZq2eoQzFgScCYTnQo/09Rlwj2Vdfy8ebd1m3UGGNcUZcIPvyqlLoGtW6jpklMTAxjx45l9OjRjBkzhoceeoiGhoZDWtedd97Ju+++2+ryJ598kqeffrrD63377bcZO3YsY8eOpVevXgwfPpyxY8dy6aWXHlKc3mbPns2IESM4+uijGTNmTFN806ZNY+XKlYe9foCVK1dyww03AFBTU8Npp53G2LFjef7557nyyitZt27dYa3/kUceafa+1tXVkZmZyW233dasXF5eHiUlJU2PFy5cyDnnnNP0+M033yQ/P5+RI0cyYsQIbr755sOKC2DVqlUcc8wxHHXUUdxwww2oaosytbW1XHbZZRxzzDGMHDmSX/3qVy3KfOtb3+Loo49uevzYY4/xl7/85bDjA5yLC5H0M378eD0ct7+8Rkfe8abW1NYf1npM51i3bl2oQ9Dk5OSmv7/++ms99dRT9c477wxhRG2bOnWqrlixosXzdXV1HV7XE088oWeccYbu2bNHVVXLy8t13rx5bW7ncH344Yc6ZcqUQ369bz1ra2v1mGOO0dra2qbnXn/9dT3xxBN18ODB2tDQ0PR8bm6uejyepsfvv/++nn322aqq+umnn+rgwYP1888/b1rv448/fshxNjr++ON16dKl2tDQoNOnT9c33nijRZlnn31WL7jgAlVVraio0NzcXN24cWPT8hdffFEvuugiHT16dNNzFRUVOnbsWL/b9Pd/BazUVvarUddrqKCwhEmDM4iPjbqTobB3z78+Y932vZ26zlH9e3PXN0cHXL5v377MmTOH448/nrvvvpuGhgZuvfVWFi5cSE1NDddeey1XX301AL/5zW945pln6NGjBzNmzODBBx/k8ssv55xzzuG8887j1ltv5dVXXyU2NpYzzjiD2bNnc/fdd9OrVy9uvvlmVq9ezaxZs6isrGTIkCHMnTuXtLQ0pk2bxsSJE3n//fcpLy/nz3/+M5MnT/Ybb15eHj/84Q955513uO6660hPT+euu+6ipqaGIUOG8Je//IVevXqxatUqfvrTn7J//34yMzOZN28e/fr144EHHuD999+nd2/nfprU1FQuu+yyFtu55pprWLFiBVVVVZx33nncc889AH7r+M9//pN77rmHmJgYUlNTKSgoYOHChcyePZu5c+dy8cUX4/F4GDt2LC+++CI/+tGPmD17Nvn5+bzzzjt+4/et54UXXtgU23vvvce4ceOIjT24O5s/fz4/+clPeOKJJ1i2bBmTJk1q97P/zW9+w+23386IESMAiI2N5cc//nGA3xz/duzYwd69e5u2f+mll7JgwQJmzJjRrJyIUFFRQV1dHVVVVcTHxzd9Jvv37+ehhx5izpw5nH/++U2vSUpKIi8vj+XLlzNhwoTDijOqEsGmkgq2lFXyo5MD71Zlos/gwYNpaGhg165dvPLKK6SmprJixQpqamo46aSTOOOMM/jiiy9YsGABH330EUlJSZSVlTVbR1lZGS+//DJffPEFIkJ5eXmL7Vx66aX8/ve/Z+rUqdx5553cc889PPLII4DTtLF8+XLeeOMN7rnnnjabmxISEvjggw8oKSnhu9/9Lu+++y7Jycn8+te/5qGHHuK2227j+uuv55VXXiErK4vnn3+e22+/nUcffZR9+/YxZMiQdt+TX/7yl6Snp1NfX8+pp57KmjVryM7O9lvHe++9l7fffpsBAwa0qHffvn156qmnmD17Nq+99lqzZSUlJdx///0t4r/zzjub1dPXkiVLGD9+fNPjqqoq/vOf//DHP/6R8vJy5s+fH1AiWLt2LTfddFO75d5//33+53/+p8XzSUlJLF26tNlz27ZtIzs7u+lxdnY227Zta/Ha8847j1deeYV+/fpRWVnJww8/THp6OgB33HEHN910E0lJLedMyc/PZ/HixZYIOqLAnY3MLhSHp44cuQebuu2477zzDmvWrOGFF14AYM+ePRQVFfHuu+9yxRVXNP1zNv7TNurduzcJCQlceeWVnH322c3aoRvXU15eztSpUwG47LLL+N73vte0/Lvf/S4A48ePZ9OmTW3GesEFFwCwbNky1q1bx0knnQTAgQMHmDRpEl9++SVr167l9NNPB6C+vp5+/fqhqgH3MPnHP/7BnDlzqKurY8eOHaxbt45Ro0b5reNJJ53E5Zdfzvnnn99Uj0C0Fr9vPX3t2LGDkSNHNj1+7bXXOOWUU0hKSuLcc8/lvvvu4+GHHyYmJsZvfTvay+aUU05h9erVAZVt/B61t73ly5cTExPD9u3b2b17N5MnT+a0005j7969rF+/nocfftjv96Bv37588cUXHYrfn6AmAhGZDjwKxABPqeqDPsvFXX4WUAlcrqofByuegkIPA9MTycuw2chM6zZs2EBMTAx9+/ZFVfn973/PmWee2azMW2+91eYOJDY2luXLl/Of//yH5557jscee4z33nsv4Bh69nS6NsfExFBXV9dm2eTkZMDZ6Zx++unMnz+/2fJPP/2U0aNH8+GHH/p97YYNGxg8eHCr69+4cSOzZ89mxYoVpKWlcfnll1NdXd1qHZ988kk++ugjXn/9dcaOHduhnaa/+H3r6SsxMbFZv/n58+ezZMkS8vLyACgtLeX999/ntNNOIyMjg927d5OZ6dxMWlZW1vT36NGjWbVqFWPGjGkzzo6cEWRnZ1NcXNz0uLi4mP79+7d47d///nemT59OXFwcffv25aSTTmLlypWUlpayatUq8vLyqKurY9euXUybNo2FCxcCzn04iYmJbcYbiKA1lItIDPA4MAMYBVwkIqN8is0Ahro/VwFPBCueA3UNfPhVKVOGZlm/ddMqj8fDrFmzuO666xARzjzzTJ544glqa2sBKCwspKKigjPOOIO5c+dSWVkJ0KJpaP/+/ezZs4ezzjqLRx55pMXOMDU1lbS0NBYvXgzAM88803R2cKhOOOEElixZwvr16wGorKyksLCQ4cOH4/F4mhJBbW0tn332GQC33XYb1157LXv3Otdm9u7dy5w5c5qtd+/evSQnJ5OamsrXX3/Nm2++2WYdv/rqKyZOnMi9995LZmYmW7duPaz42zNy5Mim1+zdu5cPPviALVu2sGnTJjZt2sTjjz/elFymTZvGM888AzhnRn/729845ZRTALjlllt44IEHmrbZ0NDAQw891GJ7jWcEvj++SQCgX79+pKSksGzZMlSVp59+mpkzZ7Yol5OTw3vvvYeqUlFRwbJlyxgxYgTXXHMN27dvZ9OmTXzwwQcMGzasKQmA83307kl0qIJ5RjABWK+qGwBE5DlgJuDdT2wm8LR7RXuZiPQRkX6quqOzg/l4y24qDthsZKalqqoqxo4dS21tLbGxsVxyySX89Kc/BeDKK69k06ZNjBs3DlUlKyuLBQsWMH36dFavXk1+fj7x8fGcddZZPPDAA03r3LdvHzNnzqS6uhpV5eGHH26x3b/+9a9NF4sHDx582F0Bs7KymDdvHhdddBE1NTUA3H///QwbNowXXniBG264gT179lBXV8eNN97I6NGjueaaa9i/fz/HH388cXFxxMXFtWgnHzNmDMcddxyjR49m8ODBTU03rdXxlltuoaioCFXl1FNPZcyYMSxatOiw4m/LjBkzuOSSSwB46aWX+MY3vtF0RgUwc+ZMfvazn1FTU8Mdd9zBNddcw5gxY1BVpk+fzsUXXwzAscceyyOPPMJFF11EZWUlIsLZZ58dyFvfpieeeILLL7+cqqoqZsyY0XSh+NVXX2XlypXce++9XHvttVxxxRUcffTRqCpXXHEFxx57bLvrXrJkCXfddddhxxi0bp7AeTjNQY2PLwEe8ynzGnCy1+P/APl+1nUVsBJYmZOT47e7VHtWbCzVy+Z+pHurDhzS601whEP3URP5vv3tb2thYWGow+hSH3/8sV588cV+l3W0+2gw+1D6a3/xvXISSBlUdY6q5qtqflbWoR3R5+elM++KCaQkBD4inzEmMjz44IPs2NHpDQlhraSkhPvuu69T1hXMpqFiYKDX42xg+yGUMcaYNg0fPpzhw4eHOowu1dgLrDME84xgBTBURAaJSDxwIfCqT5lXgUvFcQKwR4NwfcCEN/XTxc4Yc2gO5f8paGcEqlonItcBb+N0H52rqp+JyCx3+ZPAGzhdR9fjdB+9IljxmPCUkJBAaWmpDUVtTCdQdz6ChISEDr1OIu1oLD8/XztrICwTejZDmTGdq7UZykRklarm+3tNVN1ZbMJPXFxch2ZSMsZ0Pht5zRhjopwlAmOMiXKWCIwxJspF3MViEfEAmw/x5ZlASbuluherc3SwOkeHw6lzrqr6vSM34hLB4RCRla1dNe+urM7RweocHYJVZ2saMsaYKGeJwBhjoly0JYI57RfpdqzO0cHqHB2CUueoukZgjDGmpWg7IzDGGOPDEoExxkS5bpkIRGS6iHwpIutF5FY/y0VEfucuXyMi40IRZ2cKoM4/cOu6RkSWikjbM3RHgPbq7FXueBGpF5HzujK+YAikziIyTURWi8hnItL+HJFhLoDvdqqI/EtEPnHrHNGjGIvIXBHZJSJrW1ne+fuv1qYui9QfnCGvvwIGA/HAJ8AonzJnAW/izJB2AvBRqOPugjqfCKS5f8+Ihjp7lXsPZ8jz80Iddxd8zn1w5gXPcR/3DXXcXVDnXwC/dv/OAsqA+FDHfhh1ngKMA9a2srzT91/d8YxgArBeVTeo6gHgOWCmT5mZwNPqWAb0EZF+XR1oJ2q3zqq6VFV3uw+X4cwGF8kC+ZwBrgdeBHZ1ZXBBEkidvw+8pKpbAFQ10usdSJ0VSBFnQoteOImgrmvD7DyqWoBTh9Z0+v6rOyaCAcBWr8fF7nMdLRNJOlqfH+EcUUSydussIgOA7wBPdmFcwRTI5zwMSBORhSKySkQu7bLogiOQOj8GjMSZ5vZT4Ceq2tA14YVEp++/uuN8BP6mufLtIxtImUgScH1E5BScRHByUCMKvkDq/Ajwc1Wt7yaznwVS51hgPHAqkAh8KCLLVLUw2MEFSSB1PhNYDXwDGAL8W0QWq+reIMcWKp2+/+qOiaAYGOj1OBvnSKGjZSJJQPURkWOBp4AZqlraRbEFSyB1zgeec5NAJnCWiNSp6oIuibDzBfrdLlHVCqBCRAqAMUCkJoJA6nwF8KA6DejrRWQjMAJY3jUhdrlO3391x6ahFcBQERkkIvHAhcCrPmVeBS51r76fAOxR1R1dHWgnarfOIpIDvARcEsFHh97arbOqDlLVPFXNA14AfhzBSQAC+26/AkwWkVgRSQImAp93cZydKZA6b8E5A0JEjgCGAxu6NMqu1en7r253RqCqdSJyHfA2To+Duar6mYjMcpc/idOD5CxgPVCJc0QRsQKs851ABvAH9wi5TiN45MYA69ytBFJnVf1cRN4C1gANwFOq6rcbYiQI8HO+D5gnIp/iNJv8XFUjdnhqEZkPTAMyRaQYuAuIg+Dtv2yICWOMiXLdsWnIGGNMB1giMMaYKGeJwBhjopwlAmOMiXKWCIwxJspZIjBhyR0tdLXXT14bZfd3wvbmichGd1sfi8ikQ1jHUyIyyv37Fz7Llh5ujO56Gt+Xte6Im33aKT9WRM7qjG2b7su6j5qwJCL7VbVXZ5dtYx3zgNdU9QUROQOYrarHHsb6Djum9tYrIn8FClX1l22UvxzIV9XrOjsW033YGYGJCCLSS0T+4x6tfyoiLUYaFZF+IlLgdcQ82X3+DBH50H3tP0WkvR10AXCU+9qfuutaKyI3us8li8jr7vj3a0XkAvf5hSKSLyIPAoluHM+6y/a7v5/3PkJ3z0TOFZEYEfmtiKwQZ4z5qwN4Wz7EHWxMRCaIM8/Ef93fw907ce8FLnBjucCNfa67nf/6ex9NFAr12Nv2Yz/+foB6nIHEVgMv49wF39tdlolzV2XjGe1+9/dNwO3u3zFAilu2AEh2n/85cKef7c3Dna8A+B7wEc7gbZ8CyTjDG38GHAecC/zJ67Wp7u+FOEffTTF5lWmM8TvAX92/43FGkUwErgL+132+J7ASGOQnzv1e9fsnMN193BuIdf8+DXjR/fty4DGv1z8AXOz+3QdnDKLkUH/e9hPan243xITpNqpUdWzjAxGJAx4QkSk4QycMAI4Adnq9ZgUw1y27QFVXi8hUYBSwxB1aIx7nSNqf34rI/wIenBFaTwVeVmcAN0TkJWAy8BYwW0R+jdOctLgD9XoT+J2I9ASmAwWqWuU2Rx0rB2dRSwWGAht9Xp8oIquBPGAV8G+v8n8VkaE4I1HGtbL9M4BvicjN7uMEIIfIHo/IHCZLBCZS/ABn9qnxqlorIptwdmJNVLXATRRnA8+IyG+B3cC/VfWiALZxi6q+0PhARE7zV0hVC0VkPM54L78SkXdU9d5AKqGq1SKyEGfo5AuA+Y2bA65X1bfbWUWVqo4VkVTgNeBa4Hc44+28r6rfcS+sL2zl9QKcq6pfBhKviQ52jcBEilRgl5sETgFyfQuISK5b5k/An3Gm+1sGnCQijW3+SSIyLMBtFgDfdl+TjNOss1hE+gOVqvo3YLa7HV+17pmJP8/hDBQ2GWcwNdzf1zS+RkSGudv0S1X3ADcAN7uvSQW2uYsv9yq6D6eJrNHbwPXinh6JyHGtbcNED0sEJlI8C+SLyEqcs4Mv/JSZBqwWkf/itOM/qqoenB3jfBFZg5MYRgSyQVX9GOfawXKcawZPqep/gWOA5W4Tze3A/X5ePgdY03ix2Mc7OPPSvqvO9IvgzBOxDvhYnEnL/0g7Z+xuLJ/gDM38G5yzkyU41w8avQ+MarxYjHPmEOfGttZ9bKKcdR81xpgoZ2cExhgT5SwRGGNMlLNEYIwxUc4SgTHGRDlLBMYYE+UsERhjTJSzRGCMMVHu/wM4Gg3FZWbaGwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "-----------------------\n",
    "**`-8- Showing Final Scores`**\n",
    "--------------------"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "source": [
    "scores = [score_lr,score_kclf,score_svm,score_gnb,score_RFclf,score_rf,score_xgb,score_tclf]\n",
    "Models = [\"Logistic Regression\",\"KNN CLF\",\"Support Vector Machine\",\"Gaussian Navie Bayes\",\"Random Forest with GridSearch\",\"Random Forest\",\"XGBoost\",\"Decision Tree\"]    \n",
    "\n",
    "for i in range(len(Models)):\n",
    "    print(\"The accuracy score achieved using \"+Models[i]+\" is: \"+str(scores[i])+\" %\")"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "The accuracy score achieved using Logistic Regression is: 85.25 %\n",
      "The accuracy score achieved using KNN CLF is: 68.85 %\n",
      "The accuracy score achieved using Support Vector Machine is: 70.49 %\n",
      "The accuracy score achieved using Gaussian Navie Bayes is: 85.25 %\n",
      "The accuracy score achieved using Random Forest with GridSearch is: 85.25 %\n",
      "The accuracy score achieved using Random Forest is: 90.16 %\n",
      "The accuracy score achieved using XGBoost is: 81.97 %\n",
      "The accuracy score achieved using Decision Tree is: 83.61 %\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "source": [
    "sns.set(style=\"darkgrid\",rc={'figure.figsize':(20,10)})\n",
    "plt.xlabel(\"Models\",loc='center')\n",
    "plt.ylabel(\"Accuracy score\")\n",
    "\n",
    "sns.barplot(Models,scores)\n",
    "plt.savefig(\"AccuracyScores.png\")"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {}
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "-----------------------\n",
    "**`Though The Random forest Classifier gets the best result, We will use it as our main model to connect it's API with the GUI `**\n",
    "--------------------"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "source": [
    "df.describe()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>slope</th>\n",
       "      <th>ca</th>\n",
       "      <th>thal</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>54.366337</td>\n",
       "      <td>0.683168</td>\n",
       "      <td>0.966997</td>\n",
       "      <td>131.623762</td>\n",
       "      <td>246.264026</td>\n",
       "      <td>0.148515</td>\n",
       "      <td>0.528053</td>\n",
       "      <td>149.646865</td>\n",
       "      <td>0.326733</td>\n",
       "      <td>1.039604</td>\n",
       "      <td>1.399340</td>\n",
       "      <td>0.729373</td>\n",
       "      <td>2.313531</td>\n",
       "      <td>0.544554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>9.082101</td>\n",
       "      <td>0.466011</td>\n",
       "      <td>1.032052</td>\n",
       "      <td>17.538143</td>\n",
       "      <td>51.830751</td>\n",
       "      <td>0.356198</td>\n",
       "      <td>0.525860</td>\n",
       "      <td>22.905161</td>\n",
       "      <td>0.469794</td>\n",
       "      <td>1.161075</td>\n",
       "      <td>0.616226</td>\n",
       "      <td>1.022606</td>\n",
       "      <td>0.612277</td>\n",
       "      <td>0.498835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>126.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>47.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>211.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>133.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>55.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>153.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>61.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>140.000000</td>\n",
       "      <td>274.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>166.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>77.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>564.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>202.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.200000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              age         sex          cp    trestbps        chol         fbs  \\\n",
       "count  303.000000  303.000000  303.000000  303.000000  303.000000  303.000000   \n",
       "mean    54.366337    0.683168    0.966997  131.623762  246.264026    0.148515   \n",
       "std      9.082101    0.466011    1.032052   17.538143   51.830751    0.356198   \n",
       "min     29.000000    0.000000    0.000000   94.000000  126.000000    0.000000   \n",
       "25%     47.500000    0.000000    0.000000  120.000000  211.000000    0.000000   \n",
       "50%     55.000000    1.000000    1.000000  130.000000  240.000000    0.000000   \n",
       "75%     61.000000    1.000000    2.000000  140.000000  274.500000    0.000000   \n",
       "max     77.000000    1.000000    3.000000  200.000000  564.000000    1.000000   \n",
       "\n",
       "          restecg     thalach       exang     oldpeak       slope          ca  \\\n",
       "count  303.000000  303.000000  303.000000  303.000000  303.000000  303.000000   \n",
       "mean     0.528053  149.646865    0.326733    1.039604    1.399340    0.729373   \n",
       "std      0.525860   22.905161    0.469794    1.161075    0.616226    1.022606   \n",
       "min      0.000000   71.000000    0.000000    0.000000    0.000000    0.000000   \n",
       "25%      0.000000  133.500000    0.000000    0.000000    1.000000    0.000000   \n",
       "50%      1.000000  153.000000    0.000000    0.800000    1.000000    0.000000   \n",
       "75%      1.000000  166.000000    1.000000    1.600000    2.000000    1.000000   \n",
       "max      2.000000  202.000000    1.000000    6.200000    2.000000    4.000000   \n",
       "\n",
       "             thal      target  \n",
       "count  303.000000  303.000000  \n",
       "mean     2.313531    0.544554  \n",
       "std      0.612277    0.498835  \n",
       "min      0.000000    0.000000  \n",
       "25%      2.000000    0.000000  \n",
       "50%      2.000000    1.000000  \n",
       "75%      3.000000    1.000000  \n",
       "max      3.000000    1.000000  "
      ]
     },
     "metadata": {},
     "execution_count": 79
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "source": [
    "df.head()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>slope</th>\n",
       "      <th>ca</th>\n",
       "      <th>thal</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>187</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>130</td>\n",
       "      <td>204</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>172</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>236</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>178</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>354</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>163</td>\n",
       "      <td>1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  slope  \\\n",
       "0   63    1   3       145   233    1        0      150      0      2.3      0   \n",
       "1   37    1   2       130   250    0        1      187      0      3.5      0   \n",
       "2   41    0   1       130   204    0        0      172      0      1.4      2   \n",
       "3   56    1   1       120   236    0        1      178      0      0.8      2   \n",
       "4   57    0   0       120   354    0        1      163      1      0.6      2   \n",
       "\n",
       "   ca  thal  target  \n",
       "0   0     1       1  \n",
       "1   0     2       1  \n",
       "2   0     2       1  \n",
       "3   0     2       1  \n",
       "4   0     2       1  "
      ]
     },
     "metadata": {},
     "execution_count": 83
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "source": [
    "Input = (63, 1, 3,145,233,1,0,150, 0, 2.3,0,0,1)\n",
    "\n",
    "Input_array= np.asarray(Input)\n",
    "Input_reshaped = Input_array.reshape(1,-1)\n",
    "\n",
    "prediction = rf.predict(Input_reshaped)\n",
    "prediction = np.around(prediction)\n",
    "\n",
    "print(prediction)\n",
    "\n",
    "if (prediction[0]== 0):\n",
    "  print('The Person does not have a Heart Disease')\n",
    "else:\n",
    "  print(\"The Person will has a Heart Disease by %f \"%(prediction))\n"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "[1]\n",
      "The Person will has a Heart Disease by 1.000000 \n"
     ]
    }
   ],
   "metadata": {}
  }
 ],
 "metadata": {
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