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IotFile.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "0a7a07b6",
"metadata": {},
"source": [
"# IOT based Health Monitoring System using Different types of Machine Learning Algorithm."
]
},
{
"cell_type": "markdown",
"id": "7056906a",
"metadata": {},
"source": [
"# Package Importing"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "df4ea42a",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"import warnings\n",
"warnings.filterwarnings('ignore')"
]
},
{
"cell_type": "markdown",
"id": "3e43b51b",
"metadata": {},
"source": [
"# Dataset Reading"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "f80ba3dd",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Sl.No</th>\n",
" <th>Patient ID</th>\n",
" <th>Temperature Data</th>\n",
" <th>ECG Data</th>\n",
" <th>Pressure Data</th>\n",
" <th>Target</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
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" <td>2</td>\n",
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" <td>77</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>1</td>\n",
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" <td>16</td>\n",
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" <tr>\n",
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" <th>4</th>\n",
" <td>5</td>\n",
" <td>1</td>\n",
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" <td>18</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>145</th>\n",
" <td>146</td>\n",
" <td>2</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>146</th>\n",
" <td>147</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147</th>\n",
" <td>148</td>\n",
" <td>2</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>148</th>\n",
" <td>149</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>149</th>\n",
" <td>150</td>\n",
" <td>2</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>150 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" Sl.No Patient ID Temperature Data ECG Data Pressure Data Target\n",
"0 1 1 32 0 77 1\n",
"1 2 2 32 0 77 1\n",
"2 3 1 32 16 77 1\n",
"3 4 2 32 0 77 1\n",
"4 5 1 32 18 77 1\n",
".. ... ... ... ... ... ...\n",
"145 146 2 32 0 77 2\n",
"146 147 1 32 0 77 2\n",
"147 148 2 32 0 77 1\n",
"148 149 1 32 0 77 2\n",
"149 150 2 32 0 77 1\n",
"\n",
"[150 rows x 6 columns]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Input_data = pd.read_csv(\"iot_dataset.csv\")\n",
"Input_data"
]
},
{
"cell_type": "markdown",
"id": "0db0558a",
"metadata": {},
"source": [
"# Data PreProcessing"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "5488a46d",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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" vertical-align: top;\n",
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" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Sl.No</th>\n",
" <th>Patient ID</th>\n",
" <th>Temperature Data</th>\n",
" <th>ECG Data</th>\n",
" <th>Pressure Data</th>\n",
" <th>Target</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
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" <td>1</td>\n",
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" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" <td>16</td>\n",
" <td>77</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>2</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" <td>18</td>\n",
" <td>77</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Sl.No Patient ID Temperature Data ECG Data Pressure Data Target\n",
"0 1 1 32 0 77 1\n",
"1 2 2 32 0 77 1\n",
"2 3 1 32 16 77 1\n",
"3 4 2 32 0 77 1\n",
"4 5 1 32 18 77 1"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Input_data.head()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "56e26654",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Sl.No</th>\n",
" <th>Patient ID</th>\n",
" <th>Temperature Data</th>\n",
" <th>ECG Data</th>\n",
" <th>Pressure Data</th>\n",
" <th>Target</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>145</th>\n",
" <td>146</td>\n",
" <td>2</td>\n",
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" <td>0</td>\n",
" <td>77</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>146</th>\n",
" <td>147</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147</th>\n",
" <td>148</td>\n",
" <td>2</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>148</th>\n",
" <td>149</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>149</th>\n",
" <td>150</td>\n",
" <td>2</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Sl.No Patient ID Temperature Data ECG Data Pressure Data Target\n",
"145 146 2 32 0 77 2\n",
"146 147 1 32 0 77 2\n",
"147 148 2 32 0 77 1\n",
"148 149 1 32 0 77 2\n",
"149 150 2 32 0 77 1"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Input_data.tail()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "0ea26982",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 150 entries, 0 to 149\n",
"Data columns (total 6 columns):\n",
" # Column Non-Null Count Dtype\n",
"--- ------ -------------- -----\n",
" 0 Sl.No 150 non-null int64\n",
" 1 Patient ID 150 non-null int64\n",
" 2 Temperature Data 150 non-null int64\n",
" 3 ECG Data 150 non-null int64\n",
" 4 Pressure Data 150 non-null int64\n",
" 5 Target 150 non-null int64\n",
"dtypes: int64(6)\n",
"memory usage: 7.2 KB\n"
]
}
],
"source": [
"Input_data.info()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "06a68fb5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Sl.No 0\n",
"Patient ID 0\n",
"Temperature Data 0\n",
"ECG Data 0\n",
"Pressure Data 0\n",
"Target 0\n",
"dtype: int64"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Input_data.isnull().sum()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "1ec4117d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 59\n",
"1 56\n",
"2 35\n",
"Name: Target, dtype: int64"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Input_data['Target'].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "509c08d7",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(150, 6)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Input_data.shape"
]
},
{
"cell_type": "markdown",
"id": "f4b5f149",
"metadata": {},
"source": [
"# Data Visualization"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "75331258",
"metadata": {},
"outputs": [
{
"data": {
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aqXnz5tq8ebMmTZpkv1Mpz/XXXy9vb299+OGHuuGGG1SlShWFhYUpLCzMJd99XGPK9PJj4CoUdDdTQECAufHGG83kyZPN+fPnHfrPnj3bNGzY0Hh6epq6deua8ePHm1mzZuW7kyQiIsL07NnT6XoWL15sevbsaYKDg42bm5sJDAw0nTt3Nm+//bbJysoyxvy/u5kmTZqU7/267M6V33//3dx3330mMDDQ+Pn5mdtvv9389NNPhd7JsnHjxgLrGjVqlAkLCzOVKlUykszy5cuLHMdnn31moqKijJeXl/H19TVdunQxP/zwg0MfV93NlGf27NkmKirK+Pr6Gm9vb3P99debhx56yOHOpejoaNOkSZN8yyxse0kyQ4cOzbfuzZs3m9jYWFOlShXj5+dn/vGPf5g//vijwM+hc+fOxt/f33h6epqIiAjzt7/9zXz33Xf2Pv379ze+vr4FjnXHjh2mW7duxs/PzwQGBpq///3vJi0trcA7lArbRllZWSYuLs6Eh4cbb29vEx0dbbZu3er0d6AkYylI3nbOe7m5uZlq1aqZdu3ameeff97s3bs333uOHz9uHnnkEVO9enXj4+NjOnbsaL7//nsTHR1toqOjHfrOnz/fNGrUyLi7uzt8LiX97gN5bMZcdik6AFRA8fHxSkhI0OHDh3lOCVDBcGs2AACwNMIMAACwNE4zAQAAS+PIDAAAsDTCDAAAsDTCDAAAsLQyfWhe3q2SlwoJCVF6erqkP3/ALCEhQTNnztTx48cVFRWlN9980+EBTcXJzc3VwYMH5efn57JHzQMAgNJljFFmZqbCwsKK/R2xMn8CcJMmTfTdd9/Zpy993PzEiRM1efJkJSUlqUGDBnr55ZfVrVs37dq1q8AnmBbk4MGDCg8Pd3ndAACg9O3fvz/fE6QvV+Zhxs3NLd+v2Ep/JrIpU6Zo9OjR6tWrlyRp7ty5CgkJ0bx58zRo0KASLT8v9Ozfvz/fL9sCAIDy6dSpUwoPDy/RwYsyDzO7d+9WWFiYPD09FRUVpcTERNWtW1epqalKT09XTEyMva+np6eio6O1Zs2aQsNMVlaWw6/MZmZmSvrzt24IMwAAWEtJLhEp0wuAo6Ki9N577+mbb77RO++8o/T0dLVv315Hjx61XzcTEhLi8J5Lr6kpyPjx4xUQEGB/cYoJAICKrUzDTI8ePXTfffepWbNm6tq1q7788ktJf55OynN5IjPGFJnSRo0apZMnT9pf+/fvL53iAQBAuVCubs329fVVs2bNtHv3bvt1NJcfhcnIyMh3tOZSnp6e9lNKnFoCAKDiK1dhJisrSzt37lSNGjUUGRmp0NBQJScn2+dfuHBBK1euVPv27cuwSgAAUJ6U6QXAzzzzjGJjY1W7dm1lZGTo5Zdf1qlTp9S/f3/ZbDYNGzZMiYmJql+/vurXr6/ExET5+PioT58+ZVk2AAAoR8o0zPz+++/6xz/+oSNHjig4OFg333yz1q1bp4iICElSXFyczp07pyFDhtgfmvftt9+W+BkzAACg4qvwv5p96tQpBQQE6OTJk1w/AwCARTjz97tcXTMDAADgLMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwtDJ9AnBFUGfkl2VdAlBu7Z3Qs6xLcAn2c6Bw5WE/58gMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwtHITZsaPHy+bzaZhw4bZ24wxio+PV1hYmLy9vdWpUyf9/PPPZVckAAAod8pFmNm4caNmzpyp5s2bO7RPnDhRkydP1vTp07Vx40aFhoaqW7duyszMLKNKAQBAeVPmYeb06dPq27ev3nnnHQUGBtrbjTGaMmWKRo8erV69eqlp06aaO3euzp49q3nz5pVhxQAAoDwp8zAzdOhQ9ezZU127dnVoT01NVXp6umJiYuxtnp6eio6O1po1awpdXlZWlk6dOuXwAgAAFZdbWa58wYIF2rJlizZu3JhvXnp6uiQpJCTEoT0kJET79u0rdJnjx49XQkKCawsFAADlVpkdmdm/f7+efvppffDBB/Ly8iq0n81mc5g2xuRru9SoUaN08uRJ+2v//v0uqxkAAJQ/ZXZkZvPmzcrIyFDr1q3tbTk5OVq1apWmT5+uXbt2SfrzCE2NGjXsfTIyMvIdrbmUp6enPD09S69wAABQrpTZkZkuXbpo+/bt2rp1q/3Vpk0b9e3bV1u3blXdunUVGhqq5ORk+3suXLiglStXqn379mVVNgAAKGfK7MiMn5+fmjZt6tDm6+uratWq2duHDRumxMRE1a9fX/Xr11diYqJ8fHzUp0+fsigZAACUQ2V6AXBx4uLidO7cOQ0ZMkTHjx9XVFSUvv32W/n5+ZV1aQAAoJwoV2FmxYoVDtM2m03x8fGKj48vk3oAAED5V+bPmQEAALgahBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBpblfypk8++UT/+c9/lJaWpgsXLjjM27Jli0sKAwAAKAmnj8y88cYbGjhwoKpXr66UlBTddNNNqlatmvbs2aMePXqURo0AAACFcjrMvPXWW5o5c6amT58uDw8PxcXFKTk5WU899ZROnjxZGjUCAAAUyukwk5aWpvbt20uSvL29lZmZKUnq16+f5s+f79rqAAAAiuF0mAkNDdXRo0clSREREVq3bp0kKTU1VcYY11YHAABQDKfDzG233aYvvvhCkvTII49o+PDh6tatm+6//37de++9Li8QAACgKE7fzTRz5kzl5uZKkgYPHqygoCCtXr1asbGxGjx4sMsLBAAAKIrTYeb3339XeHi4fbp3797q3bu3jDHav3+/ateu7dICAQAAiuL0aabIyEgdPnw4X/uxY8cUGRnpkqIAAABKyukwY4yRzWbL13769Gl5eXm5pCgAAICSKvFpphEjRkiSbDabxowZIx8fH/u8nJwcrV+/XjfeeKPLCwQAAChKicNMSkqKpD+PzGzfvl0eHh72eR4eHmrRooWeeeYZ11cIAABQhBKHmeXLl0uSBg4cqKlTp8rf37/UigIAACgpp+9mmjNnTmnUAQAAcEWu6FezN27cqI8//rjAX81euHChSwoDAAAoCafvZlqwYIE6dOigHTt2aNGiRbp48aJ27NihZcuWKSAgoDRqBAAAKJTTYSYxMVGvv/66lixZIg8PD02dOlU7d+5U7969eWAeAAD4yzkdZn777Tf17NlTkuTp6akzZ87IZrNp+PDhmjlzpssLBAAAKIrTYSYoKEiZmZmSpJo1a+qnn36SJJ04cUJnz551bXUAAADFcPoC4FtuuUXJyclq1qyZevfuraefflrLli1TcnKyunTpUho1AgAAFMrpMDN9+nSdP39ekjRq1Ci5u7tr9erV6tWrl8aMGePyAgEAAIpyRaeZwsLC/nxzpUqKi4vT559/rsmTJyswMNCpZc2YMUPNmzeXv7+//P391a5dO3399df2+cYYxcfHKywsTN7e3urUqZN+/vlnZ0sGAAAVmNNHZk6ePKnk5GTt3btXNptNdevWVZcuXa7oicC1atXShAkTVK9ePUnS3LlzdffddyslJUVNmjTRxIkTNXnyZCUlJalBgwZ6+eWX1a1bN+3atUt+fn5Orw8AAFQ8ToWZDz74QE888YROnTrl0B4QEKC3335b999/v1Mrj42NdZh+5ZVXNGPGDK1bt06NGzfWlClTNHr0aPXq1UvSn2EnJCRE8+bN06BBg5xaFwAAqJhKfJppy5YtGjhwoO655x6lpKTo3LlzOnv2rDZt2qTY2Fj169dPP/744xUXkpOTowULFujMmTNq166dUlNTlZ6erpiYGHsfT09PRUdHa82aNVe8HgAAULGU+MjMtGnTdM899ygpKcmhvVWrVnrvvfd09uxZTZ06VbNnz3aqgO3bt6tdu3Y6f/68qlSpokWLFqlx48b2wBISEuLQPyQkRPv27St0eVlZWcrKyrJPX34UCQAAVCwlPjLzww8/FHlqZ/DgwVq9erXTBTRs2FBbt27VunXr9Pjjj6t///7asWOHfb7NZnPob4zJ13ap8ePHKyAgwP4KDw93uiYAAGAdJQ4zBw8eVIMGDQqd36BBAx04cMDpAjw8PFSvXj21adNG48ePV4sWLTR16lSFhoZKktLT0x36Z2Rk5Dtac6lRo0bp5MmT9tf+/fudrgkAAFhHicPM2bNn5eXlVeh8T09P+/NnroYxRllZWYqMjFRoaKiSk5Pt8y5cuKCVK1eqffv2RdaRd6t33gsAAFRcTt3N9M033xT6y9gnTpxweuXPP/+8evToofDwcGVmZmrBggVasWKFli5dKpvNpmHDhikxMVH169dX/fr1lZiYKB8fH/Xp08fpdQEAgIrJqTDTv3//IucXdS1LQf744w/169dPhw4dUkBAgJo3b66lS5eqW7dukqS4uDidO3dOQ4YM0fHjxxUVFaVvv/2WZ8wAAAC7EoeZ3Nxcl6981qxZRc632WyKj49XfHy8y9cNAAAqBqd/zgAAAKA8IcwAAABLI8wAAABLI8wAAABLI8wAAABLu6Iwc+LECb377rsaNWqUjh07JunPH6K8kicAAwAAXA2nnjMjSdu2bVPXrl0VEBCgvXv36rHHHlNQUJAWLVqkffv26b333iuNOgEAAArk9JGZESNGaMCAAdq9e7fDzxv06NFDq1atcmlxAAAAxXE6zGzcuLHAX8+uWbNmvh+FBAAAKG1OhxkvLy+dOnUqX/uuXbsUHBzskqIAAABKyukwc/fdd2vcuHG6ePGipD9/ciAtLU0jR47Ufffd5/ICAQAAiuJ0mHnttdd0+PBhVa9eXefOnVN0dLTq1asnPz8/vfLKK6VRIwAAQKGcvpvJ399fq1ev1rJly7Rlyxbl5uaqVatW6tq1a2nUBwAAUCSnwkx2dra8vLy0detW3XbbbbrttttKqy4AAIASceo0k5ubmyIiIpSTk1Na9QAAADjF6WtmXnjhBYcn/wIAAJQlp6+ZeeONN/Trr78qLCxMERER8vX1dZi/ZcsWlxUHAABQHKfDzD333FMKZQAAAFwZp8PM2LFjS6MOAACAK3JFv5oNAABQXjh9ZKZSpUqy2WyFzudOJwAA8FdyOswsWrTIYfrixYtKSUnR3LlzlZCQ4LLCAAAASsLpMHP33Xfna/vb3/6mJk2a6KOPPtIjjzziksIAAABKwmXXzERFRem7775z1eIAAABKxCVh5ty5c5o2bZpq1arlisUBAACUmNOnmQIDAx0uADbGKDMzUz4+Pvrggw9cWhwAAEBxnA4zr7/+ukOYqVSpkoKDgxUVFaXAwECXFgcAAFAcp8PMbbfdpvDw8AJvz05LS1Pt2rVdUhgAAEBJOH3NTGRkpA4fPpyv/ejRo4qMjHRJUQAAACXldJgxxhTYfvr0aXl5eV11QQAAAM4o8WmmESNGSJJsNptefPFF+fj42Ofl5ORo/fr1uvHGG11eIAAAQFFKHGZSUlIk/XlkZvv27fLw8LDP8/DwUIsWLfTMM8+4vkIAAIAilDjMLF++XJI0cOBATZ06Vf7+/qVWFAAAQEk5fTfTnDlzSqMOAACAK+J0mJGkjRs36uOPP1ZaWpouXLjgMG/hwoUuKQwAAKAknL6bacGCBerQoYN27NihRYsW6eLFi9qxY4eWLVumgICA0qgRAACgUE6HmcTERL3++utasmSJPDw8NHXqVO3cuVO9e/fmgXkAAOAv53SY+e2339SzZ09Jkqenp86cOSObzabhw4dr5syZLi8QAACgKE6HmaCgIGVmZkqSatasqZ9++kmSdOLECZ09e9a11QEAABTD6QuAb7nlFiUnJ6tZs2bq3bu3nn76aS1btkzJycnq0qVLadQIAABQKKfDzPTp03X+/HlJ0qhRo+Tu7q7Vq1erV69eGjNmjMsLBAAAKIpTYSY7O1tffPGFunfvLkmqVKmS4uLiFBcXVyrFAQAAFMepa2bc3Nz0+OOPKysrq7TqAQAAcIrTFwBHRUXZf6cJAACgrDl9zcyQIUP0z3/+U7///rtat24tX19fh/nNmzd3WXEAAADFcTrM3H///ZKkp556yt5ms9lkjJHNZlNOTo7rqgMAACiG02EmNTW1NOoAAAC4Ik6HmYiIiNKoAwAA4Io4fQGwJL3//vvq0KGDwsLCtG/fPknSlClTtHjxYpcWBwAAUBynw8yMGTM0YsQI3XHHHTpx4oT9GpmqVatqypQprq4PAACgSE6HmWnTpumdd97R6NGjVblyZXt7mzZttH37dpcWBwAAUBynw0xqaqpatmyZrz3vF7QBAAD+Sk6HmcjISG3dujVf+9dff63GjRu7oiYAAIASc/pupmeffVZDhw7V+fPnZYzRhg0bNH/+fI0fP17vvvtuadQIAABQKKfDzMCBA5Wdna24uDidPXtWffr0Uc2aNTV16lQ98MADpVEjAABAoZwOM5L02GOP6bHHHtORI0eUm5ur6tWru7ouAACAErmiMCNJGRkZ2rVrl2w2m2w2m4KDg11ZFwAAQIk4fQHwqVOn1K9fP4WFhSk6Olq33nqrwsLC9OCDD+rkyZOlUSMAAEChnA4zjz76qNavX68vv/xSJ06c0MmTJ7VkyRJt2rRJjz32WGnUCAAAUCinTzN9+eWX+uabb9SxY0d7W/fu3fXOO+/o9ttvd2lxAAAAxXH6yEy1atUUEBCQrz0gIECBgYEuKQoAAKCknA4zL7zwgkaMGKFDhw7Z29LT0/Xss89qzJgxLi0OAACgOE6fZpoxY4Z+/fVXRUREqHbt2pKktLQ0eXp66vDhw/r3v/9t77tlyxbXVQoAAFAAp8PMPffc47KVjx8/XgsXLtQvv/wib29vtW/fXq+++qoaNmxo72OMUUJCgmbOnKnjx48rKipKb775ppo0aeKyOgAAgHU5HWbGjh3rspWvXLlSQ4cOVdu2bZWdna3Ro0crJiZGO3bskK+vryRp4sSJmjx5spKSktSgQQO9/PLL6tatm3bt2iU/Pz+X1QIAAKzpih+aJ0mnT59Wbm6uQ5u/v3+J37906VKH6Tlz5qh69eravHmzbr31VhljNGXKFI0ePVq9evWSJM2dO1chISGaN2+eBg0adDXlAwCACsDpC4BTU1PVs2dP+fr62u9gCgwMVNWqVa/6bqa8h+4FBQXZ15Wenq6YmBh7H09PT0VHR2vNmjUFLiMrK0unTp1yeAEAgIrL6SMzffv2lSTNnj1bISEhstlsLinEGKMRI0aoY8eOatq0qaQ/75KSpJCQEIe+ISEh2rdvX4HLGT9+vBISElxSEwAAKP+cDjPbtm3T5s2bHS7SdYUnnnhC27Zt0+rVq/PNuzwwGWMKDVGjRo3SiBEj7NOnTp1SeHi4S2sFAADlh9Onmdq2bav9+/e7tIgnn3xSn3/+uZYvX65atWrZ20NDQyX9vyM0eTIyMvIdrcnj6ekpf39/hxcAAKi4nD4y8+6772rw4ME6cOCAmjZtKnd3d4f5zZs3L/GyjDF68skntWjRIq1YsUKRkZEO8yMjIxUaGqrk5GS1bNlSknThwgWtXLlSr776qrOlAwCACsjpMHP48GH99ttvGjhwoL3NZrPZT/3k5OSUeFlDhw7VvHnztHjxYvn5+dmPwAQEBMjb21s2m03Dhg1TYmKi6tevr/r16ysxMVE+Pj7q06ePs6UDAIAKyOkw8/DDD6tly5aaP3/+VV8APGPGDElSp06dHNrnzJmjAQMGSJLi4uJ07tw5DRkyxP7QvG+//ZZnzAAAAElXEGb27dunzz//XPXq1bvqlRtjiu1js9kUHx+v+Pj4q14fAACoeJy+APi2227Tjz/+WBq1AAAAOM3pIzOxsbEaPny4tm/frmbNmuW7APiuu+5yWXEAAADFcTrMDB48WJI0bty4fPOcvQAYAADgajkdZi7/LSYAAICy5PQ1M5c6f/68q+oAAAC4Ik6HmZycHL300kuqWbOmqlSpoj179kiSxowZo1mzZrm8QAAAgKI4HWZeeeUVJSUlaeLEifLw8LC3N2vWTO+++65LiwMAACiO02Hmvffe08yZM9W3b19VrlzZ3t68eXP98ssvLi0OAACgOE6HmQMHDhT4wLzc3FxdvHjRJUUBAACUlNNhpkmTJvr+++/ztX/88cf2H4MEAAD4q5T41uyHH35YU6dO1dixY9WvXz8dOHBAubm5WrhwoXbt2qX33ntPS5YsKc1aAQAA8inxkZm5c+fq3Llzio2N1UcffaSvvvpKNptNL774onbu3KkvvvhC3bp1K81aAQAA8inxkZlLfxSye/fu6t69e6kUBAAA4Aynrpmx2WylVQcAAMAVcernDBo0aFBsoDl27NhVFQQAAOAMp8JMQkKCAgICSqsWAAAApzkVZh544AFVr169tGoBAABwWomvmeF6GQAAUB6VOMxcejcTAABAeVHi00y5ubmlWQcAAMAVcfrnDAAAAMoTwgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALA0wgwAALC0Mg0zq1atUmxsrMLCwmSz2fTZZ585zDfGKD4+XmFhYfL29lanTp30888/l02xAACgXCrTMHPmzBm1aNFC06dPL3D+xIkTNXnyZE2fPl0bN25UaGiounXrpszMzL+4UgAAUF65leXKe/TooR49ehQ4zxijKVOmaPTo0erVq5ckae7cuQoJCdG8efM0aNCgv7JUAABQTpXba2ZSU1OVnp6umJgYe5unp6eio6O1Zs2aQt+XlZWlU6dOObwAAEDFVW7DTHp6uiQpJCTEoT0kJMQ+ryDjx49XQECA/RUeHl6qdQIAgLJVbsNMHpvN5jBtjMnXdqlRo0bp5MmT9tf+/ftLu0QAAFCGyvSamaKEhoZK+vMITY0aNeztGRkZ+Y7WXMrT01Oenp6lXh8AACgfyu2RmcjISIWGhio5OdneduHCBa1cuVLt27cvw8oAAEB5UqZHZk6fPq1ff/3VPp2amqqtW7cqKChItWvX1rBhw5SYmKj69eurfv36SkxMlI+Pj/r06VOGVQMAgPKkTMPMpk2b1LlzZ/v0iBEjJEn9+/dXUlKS4uLidO7cOQ0ZMkTHjx9XVFSUvv32W/n5+ZVVyQAAoJwp0zDTqVMnGWMKnW+z2RQfH6/4+Pi/rigAAGAp5faaGQAAgJIgzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEsjzAAAAEuzRJh56623FBkZKS8vL7Vu3Vrff/99WZcEAADKiXIfZj766CMNGzZMo0ePVkpKim655Rb16NFDaWlpZV0aAAAoB8p9mJk8ebIeeeQRPfroo7rhhhs0ZcoUhYeHa8aMGWVdGgAAKAfKdZi5cOGCNm/erJiYGIf2mJgYrVmzpoyqAgAA5YlbWRdQlCNHjignJ0chISEO7SEhIUpPTy/wPVlZWcrKyrJPnzx5UpJ06tSpUqkxN+tsqSwXqAhKa7/7q7GfA4Urrf08b7nGmGL7luswk8dmszlMG2PyteUZP368EhIS8rWHh4eXSm0AChcwpawrAFDaSns/z8zMVEBAQJF9ynWYue6661S5cuV8R2EyMjLyHa3JM2rUKI0YMcI+nZubq2PHjqlatWqFBqCK5NSpUwoPD9f+/fvl7+9f1uX8pa7VsV+r45YY+7U49mt13NK1N3ZjjDIzMxUWFlZs33IdZjw8PNS6dWslJyfr3nvvtbcnJyfr7rvvLvA9np6e8vT0dGirWrVqaZZZLvn7+18TX/aCXKtjv1bHLTH2a3Hs1+q4pWtr7MUdkclTrsOMJI0YMUL9+vVTmzZt1K5dO82cOVNpaWkaPHhwWZcGAADKgXIfZu6//34dPXpU48aN06FDh9S0aVN99dVXioiIKOvSAABAOVDuw4wkDRkyREOGDCnrMizB09NTY8eOzXeq7VpwrY79Wh23xNivxbFfq+OWru2xF8dmSnLPEwAAQDlVrh+aBwAAUBzCDAAAsDTCDAAAsDTCDAAAsDTCjAW89dZbioyMlJeXl1q3bq3vv/++0L4DBgyQzWbL92rSpIm9T1JSUoF9zp8//1cMp0RWrVql2NhYhYWFyWaz6bPPPiv2PStXrlTr1q3l5eWlunXr6u23387X59NPP1Xjxo3l6empxo0ba9GiRaVQ/ZVzdtwLFy5Ut27dFBwcLH9/f7Vr107ffPONQx8rbG/J+bGvWLGiwHH98ssvDv3K+zaXnB97RdnPx48fr7Zt28rPz0/Vq1fXPffco127dhX7Pqvv61cy7oq0r5cGwkw599FHH2nYsGEaPXq0UlJSdMstt6hHjx5KS0srsP/UqVN16NAh+2v//v0KCgrS3//+d4d+/v7+Dv0OHTokLy+vv2JIJXLmzBm1aNFC06dPL1H/1NRU3XHHHbrllluUkpKi559/Xk899ZQ+/fRTe5+1a9fq/vvvV79+/fTjjz+qX79+6t27t9avX19aw3Cas+NetWqVunXrpq+++kqbN29W586dFRsbq5SUFId+5X17S86PPc+uXbscxlW/fn37PCtsc8n5sVeU/XzlypUaOnSo1q1bp+TkZGVnZysmJkZnzpwp9D0VYV+/knFXpH29VBiUazfddJMZPHiwQ1ujRo3MyJEjS/T+RYsWGZvNZvbu3WtvmzNnjgkICHBlmaVKklm0aFGRfeLi4kyjRo0c2gYNGmRuvvlm+3Tv3r3N7bff7tCne/fu5oEHHnBZra5UknEXpHHjxiYhIcE+bbXtbUzJxr58+XIjyRw/frzQPlbb5sZc2XavCPu5McZkZGQYSWblypWF9qmI+3pJxl2QirCvuwpHZsqxCxcuaPPmzYqJiXFoj4mJ0Zo1a0q0jFmzZqlr1675nph8+vRpRUREqFatWrrzzjvzpXurWbt2bb7PqXv37tq0aZMuXrxYZJ+SfpZWkJubq8zMTAUFBTm0V7TtfamWLVuqRo0a6tKli5YvX+4w71rY5lLF2c9PnjwpSfm+v5eqiPt6ScZ9uWtxXy8KYaYcO3LkiHJycvL9QnhISEi+XxIvyKFDh/T111/r0UcfdWhv1KiRkpKS9Pnnn2v+/Pny8vJShw4dtHv3bpfW/1dKT08v8HPKzs7WkSNHiuxTks/SKv71r3/pzJkz6t27t72tIm5vSapRo4ZmzpypTz/9VAsXLlTDhg3VpUsXrVq1yt7nWtjmFWU/N8ZoxIgR6tixo5o2bVpov4q2r5d03Je7lvb1krDEzxlc62w2m8O0MSZfW0GSkpJUtWpV3XPPPQ7tN998s26++Wb7dIcOHdSqVStNmzZNb7zxhktqLgsFfU6Xt1/pZ2kF8+fPV3x8vBYvXqzq1avb2yvq9m7YsKEaNmxon27Xrp3279+v1157Tbfeequ9vSJvc6ni7OdPPPGEtm3bptWrVxfbtyLt686MO8+1tq+XBEdmyrHrrrtOlStXzveviYyMjHz/6ricMUazZ89Wv3795OHhUWTfSpUqqW3btpZO76GhoQV+Tm5ubqpWrVqRfYr7LK3go48+0iOPPKL//Oc/6tq1a5F9K8L2LszNN9/sMK6KvM2lirOfP/nkk/r888+1fPly1apVq8i+FWlfd2bcedjXC0aYKcc8PDzUunVrJScnO7QnJyerffv2Rb535cqV+vXXX/XII48Uux5jjLZu3aoaNWpcVb1lqV27dvk+p2+//VZt2rSRu7t7kX2K+yzLu/nz52vAgAGaN2+eevbsWWz/irC9C5OSkuIwroq6zfNYfT83xuiJJ57QwoULtWzZMkVGRhb7noqwr1/JuCX29SL99dccwxkLFiww7u7uZtasWWbHjh1m2LBhxtfX137XwsiRI02/fv3yve/BBx80UVFRBS4zPj7eLF261Pz2228mJSXFDBw40Li5uZn169eX6lickZmZaVJSUkxKSoqRZCZPnmxSUlLMvn37jDH5x71nzx7j4+Njhg8fbnbs2GFmzZpl3N3dzSeffGLv88MPP5jKlSubCRMmmJ07d5oJEyYYNzc3s27dur98fIVxdtzz5s0zbm5u5s033zSHDh2yv06cOGHvY4XtbYzzY3/99dfNokWLzP/+9z/z008/mZEjRxpJ5tNPP7X3scI2N8b5seex+n7++OOPm4CAALNixQqH7+/Zs2ftfSrivn4l465I+3ppIMxYwJtvvmkiIiKMh4eHadWqlcPte/379zfR0dEO/U+cOGG8vb3NzJkzC1zesGHDTO3atY2Hh4cJDg42MTExZs2aNaU5BKfl3XZ7+at///7GmILHvWLFCtOyZUvj4eFh6tSpY2bMmJFvuR9//LFp2LChcXd3N40aNXL4w1ceODvu6OjoIvsbY43tbYzzY3/11VfN9ddfb7y8vExgYKDp2LGj+fLLL/Mtt7xvc2Ou7PteEfbzgsYsycyZM8fepyLu61cy7oq0r5cGmzH//5VTAAAAFsQ1MwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwAAwNIIMwDKnU6dOmnYsGFlXQYAiyDMALhiAwYMkM1mk81mk7u7u+rWratnnnlGZ86cKdH7V6xYIZvNphMnTji0L1y4UC+99JLLa738l6VL0u/yMYaEhKhbt26aPXu2cnNzXVojgCtDmAFwVW6//XYdOnRIe/bs0csvv6y33npLzzzzzFUtMygoSH5+fi6q8OrljXHv3r36+uuv1blzZz399NO68847lZ2dXdblAdc8wgyAq+Lp6anQ0FCFh4erT58+6tu3rz777DNJ0gcffKA2bdrIz89PoaGh6tOnjzIyMiRJe/fuVefOnSVJgYGBstlsGjBggKT8p5kuXLiguLg41axZU76+voqKitKKFSvs85OSklS1alV98803uuGGG1SlShV7AJGk+Ph4zZ07V4sXL7YfZbn0/SUdY82aNdWqVSs9//zzWrx4sb7++mslJSVd6UcHwEUIMwBcytvbWxcvXpT0Zwh56aWX9OOPP+qzzz5TamqqPbCEh4fr008/lSTt2rVLhw4d0tSpUwtc5sCBA/XDDz9owYIF2rZtm/7+97/r9ttv1+7du+19zp49q9dee03vv/++Vq1apbS0NPsRomeeeUa9e/e2B5xDhw6pffv2VzXO2267TS1atNDChQuvajkArp5bWRcAoOLYsGGD5s2bpy5dukiSHn74Yfu8unXr6o033tBNN92k06dPq0qVKgoKCpIkVa9eXVWrVi1wmb/99pvmz5+v33//XWFhYZL+DCdLly7VnDlzlJiYKEm6ePGi3n77bV1//fWSpCeeeELjxo2TJFWpUkXe3t7KyspSaGioy8bbqFEjbdu2zWXLA3BlCDMArsqSJUtUpUoVZWdn6+LFi7r77rs1bdo0SVJKSori4+O1detWHTt2zH7BbFpamho3blyi5W/ZskXGGDVo0MChPSsrS9WqVbNP+/j42IOMJNWoUcN+Squ0GGNks9lKdR0AikeYAXBVOnfurBkzZsjd3V1hYWFyd3eXJJ05c0YxMTGKiYnRBx98oODgYKWlpal79+66cOFCiZefm5urypUra/PmzapcubLDvCpVqtj/O2+9eWw2m4wxVzGy4u3cuVORkZGlug4AxSPMALgqvr6+qlevXr72X375RUeOHNGECRMUHh4uSdq0aZNDHw8PD0lSTk5Ooctv2bKlcnJylJGRoVtuueWK6/Tw8ChyPc5atmyZtm/fruHDh7tsmQCuDBcAAygVtWvXloeHh6ZNm6Y9e/bo888/z/fsmIiICNlsNi1ZskSHDx/W6dOn8y2nQYMG6tu3rx566CEtXLhQqamp2rhxo1599VV99dVXJa6nTp062rZtm3bt2qUjR47YL1IuiaysLKWnp+vAgQPasmWLEhMTdffdd+vOO+/UQw89VOLlACgdhBkApSI4OFhJSUn6+OOP1bhxY02YMEGvvfaaQ5+aNWsqISFBI0eOVEhIiJ544okClzVnzhw99NBD+uc//6mGDRvqrrvu0vr16+1HfEriscceU8OGDdWmTRsFBwfrhx9+KPF7ly5dqho1aqhOnTq6/fbbtXz5cr3xxhtavHhxvlNfAP56NlPaJ5UBAABKEUdmAACApRFmAACApRFmAACApRFmAACApRFmAACApRFmAACApRFmAACApRFmAACApRFmAACApRFmAACApRFmAACApRFmAACApf1/+yMY+RKsEgsAAAAASUVORK5CYII=",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.bar(Input_data['Patient ID'],Input_data['Temperature Data']) \n",
"plt.title(\"Bar Chart of Temperature Data \") \n",
"plt.xlabel('Patient ID')\n",
"plt.ylabel('Temperature Data')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "2638ffa7",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.bar(Input_data['Patient ID'],Input_data['ECG Data']) \n",
"plt.title(\"Bar Chart of ECG Data\") \n",
"plt.xlabel('Patient ID')\n",
"plt.ylabel('ECG Data')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "12741c76",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.bar(Input_data['Patient ID'],Input_data['Pressure Data']) \n",
"plt.title(\"Bar Chart of Pressure Data\") \n",
"plt.xlabel('Patient ID')\n",
"plt.ylabel('Pressure Data')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "772178e1",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.bar(Input_data['Patient ID'],Input_data['Target']) \n",
"plt.title(\"Bar Chart of Targeted Data\") \n",
"plt.xlabel('Patient ID')\n",
"plt.ylabel('Targeted Data')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "5f31f126",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(Input_data['Patient ID'])\n",
"plt.title(\"Histogram of Patient ID\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "46d8f357",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(Input_data['Temperature Data'])\n",
"plt.title(\"Histogram of Temperature Data\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "b84a6615",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(Input_data['ECG Data'])\n",
"plt.title(\"Histogram of ECG Data\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "fb495ee6",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(Input_data['Pressure Data'])\n",
"plt.title(\"Histogram of Pressure Data\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "ab75a055",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# count plot on single categorical variable\n",
"sns.countplot(x ='Pressure Data', data = Input_data)\n",
" \n",
"# Show the plot\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "f6b3aa01",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# count plot on single categorical variable\n",
"sns.countplot(x ='ECG Data', data = Input_data)\n",
" \n",
"# Show the plot\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "15eab2e8",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# count plot on single categorical variable\n",
"sns.countplot(x ='Temperature Data', data = Input_data)\n",
" \n",
"# Show the plot\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "c6c11499",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# count plot on single categorical variable\n",
"sns.countplot(x ='Patient ID', data = Input_data)\n",
" \n",
"# Show the plot\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "4942cfc6",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot: xlabel='Patient ID', ylabel='Density'>"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.kdeplot(Input_data['Patient ID'])"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "538ec6be",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot: xlabel='Temperature Data', ylabel='Density'>"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.kdeplot(Input_data['Temperature Data'])"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "e808a018",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot: xlabel='ECG Data', ylabel='Density'>"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.kdeplot(Input_data['ECG Data'])"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "edfead4c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot: xlabel='Pressure Data', ylabel='Density'>"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.kdeplot(Input_data['Pressure Data'])"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "cc1ba62b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot: xlabel='Target', ylabel='Density'>"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.kdeplot(Input_data['Target'])"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "278c0095",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot: >"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 500x500 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import seaborn as sns\n",
"corr = Input_data.corr()\n",
"plt.subplots(figsize=(5,5))\n",
"sns.heatmap(corr, annot = True)"
]
},
{
"cell_type": "markdown",
"id": "e109a015",
"metadata": {},
"source": [
"# Model Implementation"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "ef8d342d",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Sl.No</th>\n",
" <th>Patient ID</th>\n",
" <th>Temperature Data</th>\n",
" <th>ECG Data</th>\n",
" <th>Pressure Data</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" <td>16</td>\n",
" <td>77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>2</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" <td>18</td>\n",
" <td>77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>145</th>\n",
" <td>146</td>\n",
" <td>2</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>146</th>\n",
" <td>147</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147</th>\n",
" <td>148</td>\n",
" <td>2</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>148</th>\n",
" <td>149</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>149</th>\n",
" <td>150</td>\n",
" <td>2</td>\n",
" <td>32</td>\n",
" <td>0</td>\n",
" <td>77</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>150 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" Sl.No Patient ID Temperature Data ECG Data Pressure Data\n",
"0 1 1 32 0 77\n",
"1 2 2 32 0 77\n",
"2 3 1 32 16 77\n",
"3 4 2 32 0 77\n",
"4 5 1 32 18 77\n",
".. ... ... ... ... ...\n",
"145 146 2 32 0 77\n",
"146 147 1 32 0 77\n",
"147 148 2 32 0 77\n",
"148 149 1 32 0 77\n",
"149 150 2 32 0 77\n",
"\n",
"[150 rows x 5 columns]"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X = Input_data.drop('Target',axis=1)\n",
"X"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "8ad056af",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 1\n",
"1 1\n",
"2 1\n",
"3 1\n",
"4 1\n",
" ..\n",
"145 2\n",
"146 2\n",
"147 1\n",
"148 2\n",
"149 1\n",
"Name: Target, Length: 150, dtype: int64"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Y = Input_data['Target']\n",
"Y "
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "9a855684",
"metadata": {},
"outputs": [],
"source": [
"from sklearn.model_selection import train_test_split\n",
"x_train1,x_test1,y_train1,y_test1 = train_test_split(X,Y,random_state=42,test_size=0.2,shuffle=True)"
]
},
{
"cell_type": "markdown",
"id": "8ec74960",
"metadata": {},
"source": [
"# Naive Bayes Algorithm"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "8ae5aa8b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy of Naive Bayes Algorithm 0.3\n"
]
}
],
"source": [
"from sklearn.naive_bayes import MultinomialNB \n",
"from sklearn import metrics\n",
"NB_Algorithm = MultinomialNB()\n",
"NB_Algorithm.fit(x_train1, y_train1)\n",
"NB_Algorithm_Prediction = NB_Algorithm.predict(x_test1)\n",
"Accuracy_NB = metrics.accuracy_score(y_test1, NB_Algorithm_Prediction)\n",
"print('Accuracy of Naive Bayes Algorithm', Accuracy_NB)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "696382c6",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 1, 0, 0, 2, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 2, 0, 0], dtype=int64)"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NB_Algorithm_Prediction"
]
},
{
"cell_type": "markdown",
"id": "0ddf50a3",
"metadata": {},
"source": [
"# Classification report and Confusion matrix of Naive Bayes Algorithm"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "73dcfae0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.27 0.78 0.40 9\n",
" 1 0.00 0.00 0.00 11\n",
" 2 0.67 0.20 0.31 10\n",
"\n",
" accuracy 0.30 30\n",
" macro avg 0.31 0.33 0.24 30\n",
"weighted avg 0.30 0.30 0.22 30\n",
"\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from sklearn.metrics import classification_report, confusion_matrix\n",
"CM_NB=confusion_matrix(y_test1, NB_Algorithm_Prediction)\n",
"sns.heatmap(CM_NB, annot=True, fmt='d', cmap='YlGnBu')\n",
"print(classification_report(y_test1, NB_Algorithm_Prediction))"
]
},
{
"cell_type": "markdown",
"id": "3e19a80d",
"metadata": {},
"source": [
"# Decision Tree Algorithm"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "edf2b7ab",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy of Decision Tree Algorithm 0.6666666666666666\n"
]
}
],
"source": [
"from sklearn.tree import DecisionTreeClassifier\n",
"from sklearn.metrics import accuracy_score\n",
"DT_Algorithm = DecisionTreeClassifier()\n",
"DT_Algorithm.fit(x_train1, y_train1)\n",
"DT_Algorithm_Prediction = DT_Algorithm.predict(x_test1)\n",
"Accuracy_DT = accuracy_score(y_test1, DT_Algorithm_Prediction)\n",
"print('Accuracy of Decision Tree Algorithm', Accuracy_DT)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "fc57daec",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 1, 2, 1, 1, 0, 2, 0, 1, 1, 2, 0, 1, 1, 0, 1, 2, 2, 0, 1, 0, 1,\n",
" 1, 1, 1, 1, 2, 1, 0, 1], dtype=int64)"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"DT_Algorithm_Prediction"
]
},
{
"cell_type": "markdown",
"id": "2f4fc372",
"metadata": {},
"source": [
"# Classification report and Confusion matrix of Decision Tree Algorithm"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "0d749966",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.75 0.67 0.71 9\n",
" 1 0.62 0.91 0.74 11\n",
" 2 0.67 0.40 0.50 10\n",
"\n",
" accuracy 0.67 30\n",
" macro avg 0.68 0.66 0.65 30\n",
"weighted avg 0.68 0.67 0.65 30\n",
"\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from sklearn.metrics import classification_report, confusion_matrix\n",
"CM_DT=confusion_matrix(y_test1, DT_Algorithm_Prediction)\n",
"sns.heatmap(CM_DT, annot=True, fmt='d', cmap='YlGnBu')\n",
"print(classification_report(y_test1, DT_Algorithm_Prediction))"
]
},
{
"cell_type": "markdown",
"id": "7223afe5",
"metadata": {},
"source": [
"# Logistic Regression Algorithm"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "528a843e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy of Logistic Regression Algorithm 0.5333333333333333\n"
]
}
],
"source": [
"from sklearn.linear_model import LogisticRegression\n",
"LR_Algorithm = LogisticRegression()\n",
"LR_Algorithm.fit(x_train1, y_train1)\n",
"LR_Algorithm_Prediction = LR_Algorithm.predict(x_test1)\n",
"Accuracy_LR = accuracy_score(y_test1, LR_Algorithm_Prediction)\n",
"print('Accuracy of Logistic Regression Algorithm', Accuracy_LR)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "cf1690b5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 1, 1, 1, 1, 0, 1, 2, 1, 1, 1, 1, 1, 0, 0, 1, 2, 1, 0, 1, 0, 0,\n",
" 1, 2, 0, 0, 2, 2, 0, 1], dtype=int64)"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"LR_Algorithm_Prediction"
]
},
{
"cell_type": "markdown",
"id": "465d29bd",
"metadata": {},
"source": [
"# Classification report and Confusion matrix of Logistic Regression Algorithm"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "96c6fbf1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.50 0.56 0.53 9\n",
" 1 0.47 0.64 0.54 11\n",
" 2 0.80 0.40 0.53 10\n",
"\n",
" accuracy 0.53 30\n",
" macro avg 0.59 0.53 0.53 30\n",
"weighted avg 0.59 0.53 0.53 30\n",
"\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from sklearn.metrics import classification_report, confusion_matrix\n",
"CM_LR=confusion_matrix(y_test1, LR_Algorithm_Prediction)\n",
"sns.heatmap(CM_LR, annot=True, fmt='d', cmap='YlGnBu')\n",
"print(classification_report(y_test1, LR_Algorithm_Prediction))"
]
},
{
"cell_type": "markdown",
"id": "c5485881",
"metadata": {},
"source": [
"# Support Vector Machine Algorithm"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "7e89e41c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy of Support Vector Machine Algorithm 0.5333333333333333\n"
]
}
],
"source": [
"from sklearn.svm import SVC\n",
"SVM_Algorithm = SVC()\n",
"SVM_Algorithm.fit(x_train1, y_train1)\n",
"SVM_Algorithm_Prediction = SVM_Algorithm.predict(x_test1)\n",
"Accuracy_SVM = accuracy_score(y_test1, LR_Algorithm_Prediction)\n",
"print('Accuracy of Support Vector Machine Algorithm', Accuracy_SVM)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "dd88ecb6",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 2, 0, 1, 0, 1,\n",
" 1, 1, 1, 1, 0, 1, 0, 0], dtype=int64)"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVM_Algorithm_Prediction"
]
},
{
"cell_type": "markdown",
"id": "c25c7973",
"metadata": {},
"source": [
"# Classification report and Confusion matrix of Support Vector Machine Algorithm"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "6103c6c8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.29 0.56 0.38 9\n",
" 1 0.50 0.55 0.52 11\n",
" 2 0.00 0.00 0.00 10\n",
"\n",
" accuracy 0.37 30\n",
" macro avg 0.26 0.37 0.30 30\n",
"weighted avg 0.27 0.37 0.31 30\n",
"\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from sklearn.metrics import classification_report, confusion_matrix\n",
"CM_SVM=confusion_matrix(y_test1, SVM_Algorithm_Prediction)\n",
"sns.heatmap(CM_SVM, annot=True, fmt='d', cmap='YlGnBu')\n",
"print(classification_report(y_test1, SVM_Algorithm_Prediction))"
]
},
{
"cell_type": "markdown",
"id": "b3af0510",
"metadata": {},
"source": [
"# Comparison Plot of all the Graph"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "0be4d6d7",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Comparison Graph of all the Algorithm')"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 500x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"model_accuracy = pd.Series(data=[Accuracy_NB,Accuracy_DT,Accuracy_LR,Accuracy_SVM], \n",
" index=['Naive Bayes','Decision Tree','Logistic Regression','Support Vector Machine'])\n",
"fig= plt.figure(figsize=(5,5))\n",
"model_accuracy.sort_values().plot.barh()\n",
"plt.title('Comparison Graph of all the Algorithm')"
]
},
{
"cell_type": "markdown",
"id": "bc5749ab",
"metadata": {},
"source": [
"# Final Prediction Model"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "9830635a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"This Patient Condition is High\n"
]
}
],
"source": [
"Final_Prediction_data = (71,1,32,0,77)\n",
"Final_Prediction_data = np.array(Final_Prediction_data)\n",
"Final_Prediction_data = Final_Prediction_data.reshape(1,-1)\n",
"Final_prediction = DT_Algorithm.predict(Final_Prediction_data)\n",
"\n",
"if Final_prediction == 0:\n",
" print(\"The Patient Condition is Low\")\n",
"elif Final_prediction == 1:\n",
" print(\"The Patient Condition is Medium\")\n",
"else:\n",
" print(\"The Patient Condition is High\")"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "c626d456",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The Patient Condition is Medium\n"
]
}
],
"source": [
"Final_Prediction_data = (10,2,32,0,77)\n",
"Final_Prediction_data = np.array(Final_Prediction_data)\n",
"Final_Prediction_data = Final_Prediction_data.reshape(1,-1)\n",
"Final_prediction = DT_Algorithm.predict(Final_Prediction_data)\n",
"\n",
"if Final_prediction == 0:\n",
" print(\"The Patient Condition is Low\")\n",
"elif Final_prediction == 1:\n",
" print(\"The Patient Condition is Medium\")\n",
"else:\n",
" print(\"The Patient Condition is High\")"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "f0ba1c17",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The Patient Condition is High\n"
]
}
],
"source": [
"Final_Prediction_data = (43,1,32,0,77)\n",
"Final_Prediction_data = np.array(Final_Prediction_data)\n",
"Final_Prediction_data = Final_Prediction_data.reshape(1,-1)\n",
"Final_prediction = DT_Algorithm.predict(Final_Prediction_data)\n",
"\n",
"if Final_prediction == 0:\n",
" print(\"The Patient Condition is Low\")\n",
"elif Final_prediction == 1:\n",
" print(\"The Patient Condition is Medium\")\n",
"else:\n",
" print(\"The Patient Condition is High\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cad6519f",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.4"
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