{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "577a50ef",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
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],
"source": [
"import numpy as np # linear algebra\n",
"import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"sns.set_style('darkgrid')\n",
"import plotly.express as ex\n",
"import plotly.graph_objs as go\n",
"import plotly.offline as pyo\n",
"from plotly.subplots import make_subplots\n",
"import plotly.figure_factory as ff\n",
"pyo.init_notebook_mode()\n",
"from imblearn.over_sampling import SMOTE\n",
"import scikitplot as skplt\n",
"\n",
"\n",
"from sklearn.pipeline import Pipeline\n",
"from sklearn.preprocessing import StandardScaler,LabelEncoder\n",
"from sklearn.model_selection import train_test_split,cross_val_score\n",
"from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n",
"\n",
"\n",
"from sklearn.linear_model import LinearRegression,LogisticRegression\n",
"from sklearn.tree import DecisionTreeRegressor,DecisionTreeClassifier\n",
"from sklearn.ensemble import RandomForestClassifier\n",
"from sklearn.svm import SVC\n",
"import os\n",
"\n",
"from sklearn.metrics import classification_report,confusion_matrix,f1_score\n",
"import warnings\n",
"warnings.filterwarnings('ignore')\n",
"\n",
"plt.rc('figure',figsize=(17,13))\n",
"sns.set_context('paper',font_scale=2)\n",
"\n",
"def set_seed(seed=31415):\n",
" np.random.seed(seed)\n",
" os.environ['PYTHONHASHSEED'] = str(seed)\n",
" os.environ['TF_DETERMINISTIC_OPS'] = '1'\n",
"set_seed()\n",
"# Import necessary libraries\n",
"import pandas as pd\n",
"from sklearn.decomposition import PCA\n",
"import matplotlib.pyplot as plt\n",
"\n",
"# Import necessary libraries\n",
"import pandas as pd\n",
"from sklearn.feature_selection import RFE\n",
"from sklearn.decomposition import PCA\n",
"from sklearn.svm import SVC\n",
"from sklearn.model_selection import train_test_split\n",
"import pandas as pd\n",
"import numpy as np\n",
"from sklearn.tree import DecisionTreeClassifier\n",
"from sklearn.ensemble import ExtraTreesClassifier\n",
"from sklearn.feature_selection import SelectKBest, chi2, RFE\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.metrics import accuracy_score\n",
"\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.ensemble import AdaBoostClassifier\n",
"from sklearn.tree import DecisionTreeClassifier\n",
"from sklearn.model_selection import cross_val_score\n",
"from sklearn.linear_model import LogisticRegression\n",
"from sklearn.ensemble import GradientBoostingClassifier\n",
"from sklearn.svm import SVC\n",
"from sklearn.ensemble import RandomForestClassifier\n",
"from sklearn.ensemble import GradientBoostingClassifier\n",
"from sklearn.neural_network import MLPClassifier\n",
"from sklearn.metrics import accuracy_score\n",
"from sklearn.metrics import confusion_matrix\n",
"from sklearn.metrics import classification_report\n",
"import matplotlib.pyplot as plt\n",
"from sklearn.metrics import roc_curve, auc\n",
"\n",
"\n",
"from sklearn.ensemble import VotingClassifier\n",
"from sklearn.svm import SVC\n",
"from sklearn.linear_model import LogisticRegression\n",
"from sklearn.ensemble import RandomForestClassifier\n",
"from datetime import datetime\n",
"import time \n",
"from datetime import timedelta\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "37bffb4b",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" id | \n",
" gender | \n",
" age | \n",
" hypertension | \n",
" heart_disease | \n",
" ever_married | \n",
" work_type | \n",
" Residence_type | \n",
" avg_glucose_level | \n",
" bmi | \n",
" smoking_status | \n",
" stroke | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" 9046 | \n",
" Male | \n",
" 67.0 | \n",
" 0 | \n",
" 1 | \n",
" Yes | \n",
" Private | \n",
" Urban | \n",
" 228.69 | \n",
" 36.6 | \n",
" formerly smoked | \n",
" 1 | \n",
"
\n",
" \n",
" 1 | \n",
" 51676 | \n",
" Female | \n",
" 61.0 | \n",
" 0 | \n",
" 0 | \n",
" Yes | \n",
" Self-employed | \n",
" Rural | \n",
" 202.21 | \n",
" NaN | \n",
" never smoked | \n",
" 1 | \n",
"
\n",
" \n",
" 2 | \n",
" 31112 | \n",
" Male | \n",
" 80.0 | \n",
" 0 | \n",
" 1 | \n",
" Yes | \n",
" Private | \n",
" Rural | \n",
" 105.92 | \n",
" 32.5 | \n",
" never smoked | \n",
" 1 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" id gender age hypertension heart_disease ever_married \\\n",
"0 9046 Male 67.0 0 1 Yes \n",
"1 51676 Female 61.0 0 0 Yes \n",
"2 31112 Male 80.0 0 1 Yes \n",
"\n",
" work_type Residence_type avg_glucose_level bmi smoking_status \\\n",
"0 Private Urban 228.69 36.6 formerly smoked \n",
"1 Self-employed Rural 202.21 NaN never smoked \n",
"2 Private Rural 105.92 32.5 never smoked \n",
"\n",
" stroke \n",
"0 1 \n",
"1 1 \n",
"2 1 "
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.read_csv('D:/Brain Stroke Prediction data/healthcare-dataset-stroke-data.csv')\n",
"df.head(3)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "17b579d1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"id 0\n",
"gender 0\n",
"age 0\n",
"hypertension 0\n",
"heart_disease 0\n",
"ever_married 0\n",
"work_type 0\n",
"Residence_type 0\n",
"avg_glucose_level 0\n",
"bmi 201\n",
"smoking_status 0\n",
"stroke 0\n",
"dtype: int64"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.isnull().sum()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "e09ed9a2",
"metadata": {},
"outputs": [],
"source": [
"df.bmi.replace(to_replace=np.nan, value=df.bmi.mean(), inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "3971679c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"id 0\n",
"gender 0\n",
"age 0\n",
"hypertension 0\n",
"heart_disease 0\n",
"ever_married 0\n",
"work_type 0\n",
"Residence_type 0\n",
"avg_glucose_level 0\n",
"bmi 0\n",
"smoking_status 0\n",
"stroke 0\n",
"dtype: int64"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.isnull().sum()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "a6fa1718",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" id | \n",
" age | \n",
" hypertension | \n",
" heart_disease | \n",
" avg_glucose_level | \n",
" bmi | \n",
" stroke | \n",
"
\n",
" \n",
" \n",
" \n",
" count | \n",
" 5110.000000 | \n",
" 5110.000000 | \n",
" 5110.000000 | \n",
" 5110.000000 | \n",
" 5110.000000 | \n",
" 5110.000000 | \n",
" 5110.000000 | \n",
"
\n",
" \n",
" mean | \n",
" 36517.829354 | \n",
" 43.226614 | \n",
" 0.097456 | \n",
" 0.054012 | \n",
" 106.147677 | \n",
" 28.893237 | \n",
" 0.048728 | \n",
"
\n",
" \n",
" std | \n",
" 21161.721625 | \n",
" 22.612647 | \n",
" 0.296607 | \n",
" 0.226063 | \n",
" 45.283560 | \n",
" 7.698018 | \n",
" 0.215320 | \n",
"
\n",
" \n",
" min | \n",
" 67.000000 | \n",
" 0.080000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 55.120000 | \n",
" 10.300000 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" 25% | \n",
" 17741.250000 | \n",
" 25.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 77.245000 | \n",
" 23.800000 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" 50% | \n",
" 36932.000000 | \n",
" 45.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 91.885000 | \n",
" 28.400000 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" 75% | \n",
" 54682.000000 | \n",
" 61.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 114.090000 | \n",
" 32.800000 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" max | \n",
" 72940.000000 | \n",
" 82.000000 | \n",
" 1.000000 | \n",
" 1.000000 | \n",
" 271.740000 | \n",
" 97.600000 | \n",
" 1.000000 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" id age hypertension heart_disease \\\n",
"count 5110.000000 5110.000000 5110.000000 5110.000000 \n",
"mean 36517.829354 43.226614 0.097456 0.054012 \n",
"std 21161.721625 22.612647 0.296607 0.226063 \n",
"min 67.000000 0.080000 0.000000 0.000000 \n",
"25% 17741.250000 25.000000 0.000000 0.000000 \n",
"50% 36932.000000 45.000000 0.000000 0.000000 \n",
"75% 54682.000000 61.000000 0.000000 0.000000 \n",
"max 72940.000000 82.000000 1.000000 1.000000 \n",
"\n",
" avg_glucose_level bmi stroke \n",
"count 5110.000000 5110.000000 5110.000000 \n",
"mean 106.147677 28.893237 0.048728 \n",
"std 45.283560 7.698018 0.215320 \n",
"min 55.120000 10.300000 0.000000 \n",
"25% 77.245000 23.800000 0.000000 \n",
"50% 91.885000 28.400000 0.000000 \n",
"75% 114.090000 32.800000 0.000000 \n",
"max 271.740000 97.600000 1.000000 "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.describe()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "d9f0aef3",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" id | \n",
" age | \n",
" hypertension | \n",
" heart_disease | \n",
" avg_glucose_level | \n",
" bmi | \n",
" stroke | \n",
"
\n",
" \n",
" \n",
" \n",
" id | \n",
" 1.000000 | \n",
" 0.003538 | \n",
" 0.003550 | \n",
" -0.001296 | \n",
" 0.001092 | \n",
" 0.002999 | \n",
" 0.006388 | \n",
"
\n",
" \n",
" age | \n",
" 0.003538 | \n",
" 1.000000 | \n",
" 0.276398 | \n",
" 0.263796 | \n",
" 0.238171 | \n",
" 0.325942 | \n",
" 0.245257 | \n",
"
\n",
" \n",
" hypertension | \n",
" 0.003550 | \n",
" 0.276398 | \n",
" 1.000000 | \n",
" 0.108306 | \n",
" 0.174474 | \n",
" 0.160189 | \n",
" 0.127904 | \n",
"
\n",
" \n",
" heart_disease | \n",
" -0.001296 | \n",
" 0.263796 | \n",
" 0.108306 | \n",
" 1.000000 | \n",
" 0.161857 | \n",
" 0.038899 | \n",
" 0.134914 | \n",
"
\n",
" \n",
" avg_glucose_level | \n",
" 0.001092 | \n",
" 0.238171 | \n",
" 0.174474 | \n",
" 0.161857 | \n",
" 1.000000 | \n",
" 0.168751 | \n",
" 0.131945 | \n",
"
\n",
" \n",
" bmi | \n",
" 0.002999 | \n",
" 0.325942 | \n",
" 0.160189 | \n",
" 0.038899 | \n",
" 0.168751 | \n",
" 1.000000 | \n",
" 0.038947 | \n",
"
\n",
" \n",
" stroke | \n",
" 0.006388 | \n",
" 0.245257 | \n",
" 0.127904 | \n",
" 0.134914 | \n",
" 0.131945 | \n",
" 0.038947 | \n",
" 1.000000 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" id age hypertension heart_disease \\\n",
"id 1.000000 0.003538 0.003550 -0.001296 \n",
"age 0.003538 1.000000 0.276398 0.263796 \n",
"hypertension 0.003550 0.276398 1.000000 0.108306 \n",
"heart_disease -0.001296 0.263796 0.108306 1.000000 \n",
"avg_glucose_level 0.001092 0.238171 0.174474 0.161857 \n",
"bmi 0.002999 0.325942 0.160189 0.038899 \n",
"stroke 0.006388 0.245257 0.127904 0.134914 \n",
"\n",
" avg_glucose_level bmi stroke \n",
"id 0.001092 0.002999 0.006388 \n",
"age 0.238171 0.325942 0.245257 \n",
"hypertension 0.174474 0.160189 0.127904 \n",
"heart_disease 0.161857 0.038899 0.134914 \n",
"avg_glucose_level 1.000000 0.168751 0.131945 \n",
"bmi 0.168751 1.000000 0.038947 \n",
"stroke 0.131945 0.038947 1.000000 "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.corr()"
]
},
{
"cell_type": "raw",
"id": "4a70261f",
"metadata": {},
"source": [
"plt.figure(figsize=(9, 8))\n",
"plt.subplot(2,1,1)\n",
"plt.title('Stroke Sample Distribution Based On Bmi And Glucose Level')\n",
"sns.scatterplot(x=df['avg_glucose_level'],y=df['bmi'],hue=df['stroke'])\n",
"plt.subplot(2,1,2)\n",
"plt.title('Stroke Sample Distribution Based On Bmi And Age')\n",
"sns.scatterplot(x=df['age'],y=df['bmi'],hue=df['stroke'])\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "raw",
"id": "7dae6a86",
"metadata": {},
"source": [
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"\n",
"# Set custom color palette\n",
"import matplotlib.colors as mcolors\n",
"plt.figure(figsize=(10, 7))\n",
"colors = ['#ff7f0e', '#1f87b4']\n",
"cmap = mcolors.ListedColormap(colors)\n",
"\n",
"# Plot correlation matrix\n",
"corr = df.corr()\n",
"sns.heatmap(corr, cmap=cmap, annot=True)\n",
"plt.title('Correlation Matrix')\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "4391463a",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import pandas as pd\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"\n",
"# Load dataset\n",
"\n",
"\n",
"# Convert smoking_status to categorical data type\n",
"df['smoking_status'] = df['smoking_status'].astype('category')\n",
"\n",
"# Remove missing or NaN values\n",
"df = df.dropna(subset=['smoking_status'])\n",
"\n",
"# Define custom colors\n",
"colors = ['#ff7f0e', '#1f77b4']\n",
"\n",
"# Create subplots\n",
"fig, axs = plt.subplots(2, 3, figsize=(16, 10))\n",
"\n",
"# Plot age histogram\n",
"sns.histplot(data=df, x='age', hue='stroke', palette=colors, ax=axs[0, 0])\n",
"axs[0, 0].set_title('Age Distribution by Stroke Status')\n",
"\n",
"# Plot BMI histogram\n",
"sns.histplot(data=df, x='bmi', hue='stroke', palette=colors, ax=axs[0, 1])\n",
"axs[0, 1].set_title('BMI Distribution by Stroke Status')\n",
"\n",
"# Plot smoking status bar chart\n",
"sns.countplot(x='ever_married', hue='stroke', data=df, palette=colors, ax=axs[0, 2])\n",
"axs[0, 2].set_title('Stroke Counts by Ever_married')\n",
"\n",
"# Plot stroke by gender\n",
"sns.countplot(x='gender', hue='stroke', data=df, palette=colors, ax=axs[1, 0])\n",
"axs[1, 0].set_title('Stroke Counts by Gender')\n",
"\n",
"# Plot stroke by hypertension\n",
"sns.countplot(x='hypertension', hue='stroke', data=df, palette=colors, ax=axs[1, 1])\n",
"axs[1, 1].set_title('Stroke Counts by Hypertension')\n",
"\n",
"# Plot stroke by heart disease\n",
"sns.countplot(x='heart_disease', hue='stroke', data=df, palette=colors, ax=axs[1, 2])\n",
"axs[1, 2].set_title('Stroke Counts by Heart Disease')\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1b9c1861",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "85f4c859",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 11,
"id": "bc4f7e9d",
"metadata": {},
"outputs": [],
"source": [
"df[\"Residence_type\"] = df[\"Residence_type\"].apply(lambda x: 1 if x==\"Urban\" else 0)\n",
"df[\"ever_married\"] = df[\"ever_married\"].apply(lambda x: 1 if x==\"Yes\" else 0)\n",
"df[\"gender\"] = df[\"gender\"].apply(lambda x: 1 if x==\"Male\" else 0)\n",
"\n",
" \n",
"df = pd.get_dummies(data=df, columns=['smoking_status'])\n",
"df = pd.get_dummies(data=df, columns=['work_type'])\n",
"\n",
"\n",
"std=StandardScaler()\n",
"columns = ['avg_glucose_level','bmi','age']\n",
"scaled = std.fit_transform(df[['avg_glucose_level','bmi','age']])\n",
"scaled = pd.DataFrame(scaled,columns=columns)\n",
"df=df.drop(columns=columns,axis=1)\n",
"\n",
"\n",
"df=df.merge(scaled, left_index=True, right_index=True, how = \"left\")\n",
"df\n",
"\n",
"df=df.drop(columns='id',axis=1)\n",
"\n",
"df[df.isnull().any(axis=1)]\n",
"\n",
"X = df.drop(['stroke'], axis=1).values \n",
"y = df['stroke'].values\n",
"\n",
"X_train1, X_test1, y_train1, y_test1=train_test_split(X, y,test_size=0.30, shuffle=True)"
]
},
{
"cell_type": "markdown",
"id": "14ba8511",
"metadata": {},
"source": [
"# SINGLE MODELS WITH ORIGINAL DATASET"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "f0ffe5c1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"LR\n",
" precision recall f1-score support\n",
"\n",
" 0 0.96 1.00 0.98 1470\n",
" 1 0.00 0.00 0.00 63\n",
"\n",
" accuracy 0.96 1533\n",
" macro avg 0.48 0.50 0.49 1533\n",
"weighted avg 0.92 0.96 0.94 1533\n",
"\n",
"[[1470 0]\n",
" [ 63 0]]\n",
"Accuracy: 0.958904\n",
"Execution time: 0.1580655574798584 secs\n",
"ETC\n",
" precision recall f1-score support\n",
"\n",
" 0 0.96 1.00 0.98 1470\n",
" 1 0.00 0.00 0.00 63\n",
"\n",
" accuracy 0.96 1533\n",
" macro avg 0.48 0.50 0.49 1533\n",
"weighted avg 0.92 0.96 0.94 1533\n",
"\n",
"[[1466 4]\n",
" [ 63 0]]\n",
"Accuracy: 0.956295\n",
"Execution time: 0.06281161308288574 secs\n",
"GBM\n",
" precision recall f1-score support\n",
"\n",
" 0 0.97 0.96 0.96 1470\n",
" 1 0.20 0.22 0.21 63\n",
"\n",
" accuracy 0.93 1533\n",
" macro avg 0.58 0.59 0.59 1533\n",
"weighted avg 0.94 0.93 0.93 1533\n",
"\n",
"[[1415 55]\n",
" [ 49 14]]\n",
"Accuracy: 0.932159\n",
"Execution time: 3.9084930419921875 secs\n",
"KNN\n",
" precision recall f1-score support\n",
"\n",
" 0 0.96 0.98 0.97 1470\n",
" 1 0.00 0.00 0.00 63\n",
"\n",
" accuracy 0.94 1533\n",
" macro avg 0.48 0.49 0.48 1533\n",
"weighted avg 0.92 0.94 0.93 1533\n",
"\n",
"[[1439 31]\n",
" [ 63 0]]\n",
"Accuracy: 0.938682\n",
"Execution time: 0.22194218635559082 secs\n",
"SVC\n",
" precision recall f1-score support\n",
"\n",
" 0 0.96 0.96 0.96 1470\n",
" 1 0.08 0.08 0.08 63\n",
"\n",
" accuracy 0.92 1533\n",
" macro avg 0.52 0.52 0.52 1533\n",
"weighted avg 0.92 0.92 0.92 1533\n",
"\n",
"[[1410 60]\n",
" [ 58 5]]\n",
"Accuracy: 0.923027\n",
"Execution time: 0.9076035022735596 secs\n",
"ADA\n",
" precision recall f1-score support\n",
"\n",
" 0 0.96 0.99 0.98 1470\n",
" 1 0.18 0.03 0.05 63\n",
"\n",
" accuracy 0.95 1533\n",
" macro avg 0.57 0.51 0.52 1533\n",
"weighted avg 0.93 0.95 0.94 1533\n",
"\n",
"[[1461 9]\n",
" [ 61 2]]\n",
"Accuracy: 0.954338\n",
"Execution time: 0.7407827377319336 secs\n",
"DT\n",
" precision recall f1-score support\n",
"\n",
" 0 0.97 0.95 0.96 1470\n",
" 1 0.18 0.24 0.21 63\n",
"\n",
" accuracy 0.92 1533\n",
" macro avg 0.57 0.60 0.58 1533\n",
"weighted avg 0.93 0.92 0.93 1533\n",
"\n",
"[[1402 68]\n",
" [ 48 15]]\n",
"Accuracy: 0.924331\n",
"Execution time: 0.033911943435668945 secs\n",
"SGD\n",
" precision recall f1-score support\n",
"\n",
" 0 0.96 0.97 0.97 1470\n",
" 1 0.05 0.03 0.04 63\n",
"\n",
" accuracy 0.94 1533\n",
" macro avg 0.50 0.50 0.50 1533\n",
"weighted avg 0.92 0.94 0.93 1533\n",
"\n",
"[[1432 38]\n",
" [ 61 2]]\n",
"Accuracy: 0.935421\n",
"Execution time: 0.015437841415405273 secs\n",
"RF\n",
" precision recall f1-score support\n",
"\n",
" 0 0.96 1.00 0.98 1470\n",
" 1 0.00 0.00 0.00 63\n",
"\n",
" accuracy 0.95 1533\n",
" macro avg 0.48 0.50 0.49 1533\n",
"weighted avg 0.92 0.95 0.94 1533\n",
"\n",
"[[1464 6]\n",
" [ 63 0]]\n",
"Accuracy: 0.954990\n",
"Execution time: 0.07191610336303711 secs\n"
]
}
],
"source": [
"\n",
"#machine learning models\n",
"\n",
"##########2\n",
"start_time = time.time()\n",
"from sklearn.linear_model import LogisticRegression\n",
"print(\"LR\")\n",
"lr = LogisticRegression(random_state=300, solver='newton-cg',multi_class='multinomial',C=1.0)\n",
"lr.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = lr.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"#########3\n",
"start_time = time.time()\n",
"from sklearn.ensemble import ExtraTreesClassifier\n",
"print(\"ETC\")\n",
"etc = ExtraTreesClassifier(n_estimators=10,random_state=150,max_samples=0.5, max_depth=50,bootstrap=True)\n",
"etc.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = etc.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"#######4\n",
"import time # this is an inbuilt library in Python\n",
"start_time = time.time()\n",
"from sklearn.ensemble import GradientBoostingClassifier\n",
"print(\"GBM\")\n",
"gbm = GradientBoostingClassifier(n_estimators=100, random_state=50, max_depth=100)\n",
"gbm.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = gbm.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"########5\n",
"import time # this is an inbuilt library in Python\n",
"start_time = time.time()\n",
"from sklearn.neighbors import KNeighborsClassifier\n",
"print(\"KNN\")\n",
"knn = KNeighborsClassifier(n_neighbors=3)\n",
"knn.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = knn.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"#######6\n",
"start_time = time.time()\n",
"from sklearn.svm import SVC\n",
"print(\"SVC\")\n",
"svm = SVC(kernel='sigmoid', C=2.0, random_state=100,probability=True)\n",
"svm.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = svm.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"########7\n",
"start_time = time.time()\n",
"from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier\n",
"from sklearn.svm import SVC\n",
"print(\"ADA\")\n",
"ada = AdaBoostClassifier(n_estimators=100, random_state=50)\n",
"ada.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = ada.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"########8\n",
"start_time = time.time()\n",
"from sklearn.tree import DecisionTreeClassifier\n",
"dt = DecisionTreeClassifier(random_state=50, max_depth=100)\n",
"print(\"DT\")\n",
"dt.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = dt.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"\n",
"###9\n",
"start_time = time.time()\n",
"from sklearn.linear_model import SGDClassifier\n",
"sgd = SGDClassifier(loss=\"modified_huber\", penalty=\"l2\", max_iter=5)\n",
"print(\"SGD\")\n",
"sgd.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = sgd.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"\n",
"#########1\n",
"start_time = time.time()\n",
"from sklearn.ensemble import RandomForestClassifier, VotingClassifier\n",
"print(\"RF\")\n",
"rfc = RandomForestClassifier(n_estimators=10,random_state=150,max_samples=0.5, max_depth=50) \n",
"rfc.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = rfc.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "262aafed",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
" #Get the predicted probabilities for each classifier on the test data\n",
"from sklearn.metrics import accuracy_score, roc_auc_score\n",
"lr_probs = lr.predict_proba(X_test1)\n",
"etc_probs = etc.predict_proba(X_test1)\n",
"gbm_probs = gbm.predict_proba(X_test1)\n",
"knn_probs = knn.predict_proba(X_test1)\n",
"svm_probs = svm.predict_proba(X_test1)\n",
"ada_probs = ada.predict_proba(X_test1)\n",
"dt_probs = dt.predict_proba(X_test1)\n",
"rfc_probs = rfc.predict_proba(X_test1)\n",
"sgd_probs = sgd.predict_proba(X_test1)\n",
"\n",
"# Get the true positive rate and false positive rate for each classifier at different probability thresholds\n",
"lr_fpr, lr_tpr, _ = roc_curve(y_test1, lr_probs[:, 1])\n",
"etc_fpr, etc_tpr, _ = roc_curve(y_test1, etc_probs[:, 1])\n",
"gbm_fpr, gbm_tpr, _ = roc_curve(y_test1, gbm_probs[:, 1])\n",
"knn_fpr, knn_tpr, _ = roc_curve(y_test1, knn_probs[:, 1])\n",
"svm_fpr, svm_tpr, _ = roc_curve(y_test1, svm_probs[:, 1])\n",
"ada_fpr, ada_tpr, _ = roc_curve(y_test1, ada_probs[:, 1])\n",
"dt_fpr, dt_tpr, _ = roc_curve(y_test1, dt_probs[:, 1])\n",
"rfc_fpr, rfc_tpr, _ = roc_curve(y_test1, rfc_probs[:, 1])\n",
"sgd_fpr, sgd_tpr, _ = roc_curve(y_test1, sgd_probs[:, 1])\n",
"\n",
"# Calculate the area under the ROC curve for each classifier\n",
"lr_auc = roc_auc_score(y_test1, lr_probs[:, 1])\n",
"etc_auc = roc_auc_score(y_test1, etc_probs[:, 1])\n",
"gbm_auc = roc_auc_score(y_test1, gbm_probs[:, 1])\n",
"knn_auc = roc_auc_score(y_test1, knn_probs[:, 1])\n",
"svm_auc = roc_auc_score(y_test1, svm_probs[:, 1])\n",
"ada_auc = roc_auc_score(y_test1, ada_probs[:, 1])\n",
"\n",
"dt_auc = roc_auc_score(y_test1, lr_probs[:, 1])\n",
"rfc_auc = roc_auc_score(y_test1, rfc_probs[:, 1])\n",
"sgd_auc = roc_auc_score(y_test1, sgd_probs[:, 1])\n",
"\n",
"\n",
"# Plot the ROC curves\n",
"plt.figure(figsize=(10, 4.7))\n",
"plt.plot(lr_fpr, lr_tpr, label=f'LR (AUC = {lr_auc:.2f})')\n",
"plt.plot(etc_fpr, etc_tpr, label=f'ETC (AUC = {etc_auc:.2f})')\n",
"plt.plot(gbm_fpr, gbm_tpr, label=f'GBM (AUC = {gbm_auc:.2f})')\n",
"\n",
"plt.plot(knn_fpr, knn_tpr, label=f'KNN (AUC = {knn_auc:.2f})')\n",
"plt.plot(svm_fpr, svm_tpr, label=f'SVM (AUC = {svm_auc:.2f})')\n",
"plt.plot(ada_fpr, ada_tpr, label=f'ADA (AUC = {ada_auc:.2f})')\n",
"\n",
"plt.plot(dt_fpr, dt_tpr, label=f'DT (AUC = {dt_auc:.2f})')\n",
"plt.plot(rfc_fpr, rfc_tpr, label=f'RF (AUC = {rfc_auc:.2f})')\n",
"plt.plot(sgd_fpr, sgd_tpr, label=f'SGD (AUC = {sgd_auc:.2f})')\n",
"\n",
"plt.plot([0, 1], [0, 1], linestyle='--', label='Random Guessing')\n",
"plt.xlabel('False Positive Rate')\n",
"plt.ylabel('True Positive Rate')\n",
"plt.title('ROC Curves using Original Dataset')\n",
"plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7e7ecff8",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "ab1f38a1",
"metadata": {},
"source": [
"# ENSEMBLE USING STACKING TECHNIQUE"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "767a41ff",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.96 0.99 0.98 1470\n",
" 1 0.00 0.00 0.00 63\n",
"\n",
" accuracy 0.95 1533\n",
" macro avg 0.48 0.50 0.49 1533\n",
"weighted avg 0.92 0.95 0.94 1533\n",
"\n",
"[[1462 8]\n",
" [ 63 0]]\n",
"Accuracy: 0.953686\n"
]
}
],
"source": [
"from sklearn.model_selection import train_test_split, cross_val_predict\n",
"from sklearn.tree import DecisionTreeClassifier, ExtraTreeClassifier\n",
"from sklearn.ensemble import RandomForestClassifier, StackingClassifier\n",
"from sklearn.pipeline import make_pipeline\n",
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.metrics import accuracy_score\n",
"\n",
"# Load the Stroke Prediction dataset\n",
"#data = pd.read_csv('stroke_data.csv')\n",
"\n",
"\n",
"# Define base classifiers\n",
"dt = DecisionTreeClassifier(random_state=42)\n",
"et = ExtraTreeClassifier(random_state=42)\n",
"rf = RandomForestClassifier(n_estimators=100, random_state=42)\n",
"\n",
"# Define the stacking ensemble\n",
"estimators = [('dt', dt), ('et', et), ('rf', rf)]\n",
"stacked = StackingClassifier(estimators=estimators, final_estimator=RandomForestClassifier(random_state=42))\n",
"\n",
"# Define the pipeline for preprocessing and classification\n",
"pipeline1 = make_pipeline(StandardScaler(), stacked)\n",
"\n",
"# Use cross-validation to fit the stacking ensemble\n",
"stacked_preds = cross_val_predict(pipeline1, X_train1, y_train1, cv=5)\n",
"\n",
"# Evaluate the ensemble on the test set\n",
"pipeline1.fit(X_train1, y_train1)\n",
"stacked_test_preds = pipeline1.predict(X_test1)\n",
"\n",
"print(classification_report(y_test1, stacked_test_preds))\n",
"print(confusion_matrix(y_test1, stacked_test_preds))\n",
"accuracy = accuracy_score(y_test1, stacked_test_preds)\n",
"print('Accuracy: %f' % accuracy)\n"
]
},
{
"cell_type": "markdown",
"id": "db1237bb",
"metadata": {},
"source": [
"# ENSEMBLE USING HARD VOTING"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "af3ae7ad",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.96 0.99 0.98 1470\n",
" 1 0.18 0.05 0.07 63\n",
"\n",
" accuracy 0.95 1533\n",
" macro avg 0.57 0.52 0.53 1533\n",
"weighted avg 0.93 0.95 0.94 1533\n",
"\n",
"[[1456 14]\n",
" [ 60 3]]\n",
"Accuracy: 0.951729\n"
]
}
],
"source": [
"# Create individual models\n",
"model1 = DecisionTreeClassifier(random_state=42)\n",
"model2 = ExtraTreeClassifier(random_state=42)\n",
"model3 = RandomForestClassifier(n_estimators=100, random_state=42)\n",
"# Create ensemble model with Voting Classifier\n",
"ensemble_model_h = VotingClassifier(estimators=[('svm', model1), ('dt', model2), ('rf', model3)], voting='hard')\n",
"\n",
"# Fit the ensemble model to the training data\n",
"ensemble_model_h.fit(X_train1, y_train1)\n",
"\n",
"# Predict on test data using the ensemble model\n",
"y_pred = ensemble_model_h.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred))\n",
"print(confusion_matrix(y_test1, y_pred))\n",
"accuracy = accuracy_score(y_test1, y_pred)\n",
"print('Accuracy: %f' % accuracy)"
]
},
{
"cell_type": "markdown",
"id": "85f5c63d",
"metadata": {},
"source": [
"# ENSEMBLE USING SOFT VOTING"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "dd738b36",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.96 0.99 0.98 1470\n",
" 1 0.18 0.05 0.07 63\n",
"\n",
" accuracy 0.95 1533\n",
" macro avg 0.57 0.52 0.53 1533\n",
"weighted avg 0.93 0.95 0.94 1533\n",
"\n",
"[[1456 14]\n",
" [ 60 3]]\n",
"Accuracy: 0.951729\n"
]
}
],
"source": [
"# Create individual models\n",
"model1 = DecisionTreeClassifier(random_state=42)\n",
"model2 = ExtraTreeClassifier(random_state=42)\n",
"model3 = RandomForestClassifier(n_estimators=100, random_state=42)\n",
"# Create ensemble model with Voting Classifier\n",
"ensemble_model_s = VotingClassifier(estimators=[('svm', model1), ('dt', model2), ('rf', model3)], voting='soft')\n",
"\n",
"# Fit the ensemble model to the training data\n",
"ensemble_model_s.fit(X_train1, y_train1)\n",
"\n",
"# Predict on test data using the ensemble model\n",
"y_pred = ensemble_model_s.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred))\n",
"print(confusion_matrix(y_test1, y_pred))\n",
"accuracy = accuracy_score(y_test1, y_pred)\n",
"print('Accuracy: %f' % accuracy)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "87ae7f40",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 17,
"id": "eeca265a",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
" #Get the predicted probabilities for each classifier on the test data\n",
"pipeline1_probs = pipeline1.predict_proba(X_test1)\n",
"ensemble_model_s_probs = ensemble_model_s.predict_proba(X_test1)\n",
"#ensemble_model_h_probs = ensemble_model_h.predict_proba(X_test1)\n",
"\n",
"\n",
"# Get the true positive rate and false positive rate for each classifier at different probability thresholds\n",
"pipeline1_fpr, pipeline1_tpr, _ = roc_curve(y_test1, pipeline1_probs[:, 1])\n",
"ensemble_model_s_fpr, ensemble_model_s_tpr, _ = roc_curve(y_test1, ensemble_model_s_probs[:, 1])\n",
"#ensemble_model_h_fpr, ensemble_model_h_tpr, _ = roc_curve(y_test1, ensemble_model_h_probs[:, 1])\n",
"\n",
"\n",
"# Calculate the area under the ROC curve for each classifier\n",
"pipeline1_auc = roc_auc_score(y_test1, pipeline1_probs[:, 1])\n",
"ensemble_model_s_auc = roc_auc_score(y_test1, ensemble_model_s_probs[:, 1])\n",
"#ensemble_model_h_auc = roc_auc_score(y_test1, ensemble_model_h_probs[:, 1])\n",
"\n",
"\n",
"\n",
"# Plot the ROC curves\n",
"plt.figure(figsize=(8, 4))\n",
"plt.plot(pipeline1_fpr, pipeline1_tpr, label=f'Ensemble via Stacking (AUC = {pipeline1_auc:.2f})')\n",
"plt.plot(ensemble_model_s_fpr, ensemble_model_s_tpr, label=f'Ensemble via Voting Classifier (AUC = {ensemble_model_s_auc:.2f})')\n",
"#plt.plot(ensemble_model_h_fpr, ensemble_model_h_tpr, label=f'H (AUC = {ensemble_model_h_auc:.2f})')\n",
"\n",
"plt.plot([0, 1], [0, 1], linestyle='--', label='Random Guessing')\n",
"plt.xlabel('False Positive Rate')\n",
"plt.ylabel('True Positive Rate')\n",
"plt.title('ROC Curves using Original Dataset')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "9e97bb71",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Stacked ensemble accuracy (train): 0.9435280961699748\n",
"Stacked ensemble accuracy (test): 0.9536855838225701\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"from sklearn.datasets import load_iris\n",
"from sklearn.model_selection import train_test_split, learning_curve, cross_val_predict\n",
"from sklearn.tree import DecisionTreeClassifier, ExtraTreeClassifier\n",
"from sklearn.ensemble import RandomForestClassifier, StackingClassifier\n",
"from sklearn.pipeline import make_pipeline\n",
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.metrics import accuracy_score\n",
"\n",
"\n",
"# Split the data into training and testing sets\n",
"\n",
"# Define base classifiers\n",
"dt = DecisionTreeClassifier(random_state=42)\n",
"et = ExtraTreeClassifier(random_state=42)\n",
"rf = RandomForestClassifier(n_estimators=100, random_state=42)\n",
"\n",
"# Define the stacking ensemble\n",
"estimators = [('dt', dt), ('et', et), ('rf', rf)]\n",
"stacked = StackingClassifier(estimators=estimators, final_estimator=RandomForestClassifier(random_state=42))\n",
"\n",
"# Define the pipeline for preprocessing and classification\n",
"pipeline = make_pipeline(StandardScaler(), stacked)\n",
"\n",
"# Use cross-validation to fit the stacking ensemble\n",
"stacked_preds = cross_val_predict(pipeline, X_train1, y_train1, cv=5)\n",
"\n",
"# Evaluate the ensemble on the test set\n",
"pipeline.fit(X_train1, y_train1)\n",
"stacked_test_preds = pipeline.predict(X_test1)\n",
"\n",
"# Print the training and testing accuracy\n",
"train_accuracy = accuracy_score(y_train1, stacked_preds)\n",
"test_accuracy = accuracy_score(y_test1, stacked_test_preds)\n",
"print(\"Stacked ensemble accuracy (train):\", train_accuracy)\n",
"print(\"Stacked ensemble accuracy (test):\", test_accuracy)\n",
"\n",
"# Plot the learning curves\n",
"train_sizes, train_scores, test_scores = learning_curve(pipeline, X_train1, y_train1, cv=5, train_sizes=np.linspace(0.1, 1.0, 10), scoring='accuracy')\n",
"train_mean = np.mean(train_scores, axis=1)\n",
"train_std = np.std(train_scores, axis=1)\n",
"test_mean = np.mean(test_scores, axis=1)\n",
"test_std = np.std(test_scores, axis=1)\n",
"plt.figure(figsize=(7, 4))\n",
"plt.plot(train_sizes, train_mean, color='blue', marker='o', markersize=5, label='Training accuracy')\n",
"plt.fill_between(train_sizes, train_mean + train_std, train_mean - train_std, alpha=0.15, color='blue')\n",
"plt.plot(train_sizes, test_mean, color='green', linestyle='--', marker='s', markersize=5, label='Testing accuracy')\n",
"plt.fill_between(train_sizes, test_mean + test_std, test_mean - test_std, alpha=0.15, color='green')\n",
"plt.grid()\n",
"plt.xlabel(' Training samples')\n",
"plt.ylabel('Accuracy')\n",
"plt.legend(loc='lower right')\n",
"plt.ylim([0.88, 1.02])\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7e6b16e4",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "286d805d",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "3a2f2981",
"metadata": {},
"source": [
"# SINGLE MODELS ON SMOTED DATA"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "c4b504ee",
"metadata": {},
"outputs": [],
"source": [
"from imblearn.over_sampling import SMOTE\n",
"X_train1, X_test1, y_train1, y_test1 = train_test_split(X_resampled, y_resampled, test_size=0.3)\n",
"sm = SMOTE(random_state=2)\n",
"x_train_res, y_train_res = sm.fit_resample(X, y.ravel())\n",
"X_train1, X_test1, y_train1, y_test1 = train_test_split(x_train_res, y_train_res, test_size=0.3)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "10e3fe73",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"LR\n",
" precision recall f1-score support\n",
"\n",
" 0 0.82 0.73 0.77 1492\n",
" 1 0.75 0.84 0.79 1425\n",
"\n",
" accuracy 0.78 2917\n",
" macro avg 0.78 0.78 0.78 2917\n",
"weighted avg 0.79 0.78 0.78 2917\n",
"\n",
"[[1087 405]\n",
" [ 233 1192]]\n",
"Accuracy: 0.781282\n",
"Execution time: 0.471738338470459 secs\n",
"ETC\n",
" precision recall f1-score support\n",
"\n",
" 0 1.00 0.95 0.97 1492\n",
" 1 0.95 1.00 0.97 1425\n",
"\n",
" accuracy 0.97 2917\n",
" macro avg 0.97 0.97 0.97 2917\n",
"weighted avg 0.97 0.97 0.97 2917\n",
"\n",
"[[1412 80]\n",
" [ 0 1425]]\n",
"Accuracy: 0.972575\n",
"Execution time: 0.12369918823242188 secs\n",
"GBM\n",
" precision recall f1-score support\n",
"\n",
" 0 1.00 0.95 0.97 1492\n",
" 1 0.95 1.00 0.97 1425\n",
"\n",
" accuracy 0.97 2917\n",
" macro avg 0.97 0.97 0.97 2917\n",
"weighted avg 0.97 0.97 0.97 2917\n",
"\n",
"[[1410 82]\n",
" [ 0 1425]]\n",
"Accuracy: 0.971889\n",
"Execution time: 4.984637260437012 secs\n",
"KNN\n",
" precision recall f1-score support\n",
"\n",
" 0 1.00 0.89 0.94 1492\n",
" 1 0.90 1.00 0.95 1425\n",
"\n",
" accuracy 0.95 2917\n",
" macro avg 0.95 0.95 0.95 2917\n",
"weighted avg 0.95 0.95 0.95 2917\n",
"\n",
"[[1334 158]\n",
" [ 0 1425]]\n",
"Accuracy: 0.945835\n",
"Execution time: 0.5325472354888916 secs\n",
"SVC\n",
" precision recall f1-score support\n",
"\n",
" 0 0.64 0.63 0.64 1492\n",
" 1 0.62 0.62 0.62 1425\n",
"\n",
" accuracy 0.63 2917\n",
" macro avg 0.63 0.63 0.63 2917\n",
"weighted avg 0.63 0.63 0.63 2917\n",
"\n",
"[[945 547]\n",
" [537 888]]\n",
"Accuracy: 0.628385\n",
"Execution time: 11.657976150512695 secs\n",
"ADA\n",
" precision recall f1-score support\n",
"\n",
" 0 0.88 0.73 0.80 1492\n",
" 1 0.76 0.89 0.82 1425\n",
"\n",
" accuracy 0.81 2917\n",
" macro avg 0.82 0.81 0.81 2917\n",
"weighted avg 0.82 0.81 0.81 2917\n",
"\n",
"[[1089 403]\n",
" [ 154 1271]]\n",
"Accuracy: 0.809050\n",
"Execution time: 1.1522822380065918 secs\n",
"DT\n",
" precision recall f1-score support\n",
"\n",
" 0 1.00 0.94 0.97 1492\n",
" 1 0.94 1.00 0.97 1425\n",
"\n",
" accuracy 0.97 2917\n",
" macro avg 0.97 0.97 0.97 2917\n",
"weighted avg 0.97 0.97 0.97 2917\n",
"\n",
"[[1409 83]\n",
" [ 0 1425]]\n",
"Accuracy: 0.971546\n",
"Execution time: 0.04790830612182617 secs\n",
"SGD\n",
" precision recall f1-score support\n",
"\n",
" 0 0.64 0.79 0.71 1492\n",
" 1 0.71 0.53 0.61 1425\n",
"\n",
" accuracy 0.66 2917\n",
" macro avg 0.67 0.66 0.66 2917\n",
"weighted avg 0.67 0.66 0.66 2917\n",
"\n",
"[[1176 316]\n",
" [ 668 757]]\n",
"Accuracy: 0.662667\n",
"Execution time: 0.02492666244506836 secs\n",
"RF\n",
" precision recall f1-score support\n",
"\n",
" 0 1.00 0.95 0.98 1492\n",
" 1 0.95 1.00 0.98 1425\n",
"\n",
" accuracy 0.98 2917\n",
" macro avg 0.98 0.98 0.98 2917\n",
"weighted avg 0.98 0.98 0.98 2917\n",
"\n",
"[[1422 70]\n",
" [ 0 1425]]\n",
"Accuracy: 0.976003\n",
"Execution time: 0.09175324440002441 secs\n"
]
}
],
"source": [
"\n",
"#machine learning models\n",
"\n",
"##########2\n",
"start_time = time.time()\n",
"from sklearn.linear_model import LogisticRegression\n",
"print(\"LR\")\n",
"lr = LogisticRegression(random_state=300, solver='newton-cg',multi_class='multinomial',C=1.0)\n",
"lr.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = lr.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"#########3\n",
"start_time = time.time()\n",
"from sklearn.ensemble import ExtraTreesClassifier\n",
"print(\"ETC\")\n",
"etc = ExtraTreesClassifier(n_estimators=10,random_state=150,max_samples=0.5, max_depth=50,bootstrap=True)\n",
"etc.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = etc.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"#######4\n",
"import time # this is an inbuilt library in Python\n",
"start_time = time.time()\n",
"from sklearn.ensemble import GradientBoostingClassifier\n",
"print(\"GBM\")\n",
"gbm = GradientBoostingClassifier(n_estimators=100, random_state=50, max_depth=100)\n",
"gbm.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = gbm.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"########5\n",
"import time # this is an inbuilt library in Python\n",
"start_time = time.time()\n",
"from sklearn.neighbors import KNeighborsClassifier\n",
"print(\"KNN\")\n",
"knn = KNeighborsClassifier(n_neighbors=3)\n",
"knn.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = knn.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"#######6\n",
"start_time = time.time()\n",
"from sklearn.svm import SVC\n",
"print(\"SVC\")\n",
"svm = SVC(kernel='sigmoid', C=2.0, random_state=100,probability=True)\n",
"svm.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = svm.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"########7\n",
"start_time = time.time()\n",
"from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier\n",
"from sklearn.svm import SVC\n",
"print(\"ADA\")\n",
"ada = AdaBoostClassifier(n_estimators=100, random_state=50)\n",
"ada.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = ada.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"########8\n",
"start_time = time.time()\n",
"from sklearn.tree import DecisionTreeClassifier\n",
"dt = DecisionTreeClassifier(random_state=50, max_depth=100)\n",
"print(\"DT\")\n",
"dt.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = dt.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"\n",
"###9\n",
"start_time = time.time()\n",
"from sklearn.linear_model import SGDClassifier\n",
"sgd = SGDClassifier(loss=\"modified_huber\", penalty=\"l2\", max_iter=5)\n",
"print(\"SGD\")\n",
"sgd.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = sgd.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"\n",
"#########1\n",
"start_time = time.time()\n",
"from sklearn.ensemble import RandomForestClassifier, VotingClassifier\n",
"print(\"RF\")\n",
"rfc = RandomForestClassifier(n_estimators=10,random_state=150,max_samples=0.5, max_depth=50) \n",
"rfc.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = rfc.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "7060c351",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
" #Get the predicted probabilities for each classifier on the test data\n",
"lr_probs = lr.predict_proba(X_test1)\n",
"etc_probs = etc.predict_proba(X_test1)\n",
"gbm_probs = gbm.predict_proba(X_test1)\n",
"knn_probs = knn.predict_proba(X_test1)\n",
"svm_probs = svm.predict_proba(X_test1)\n",
"ada_probs = ada.predict_proba(X_test1)\n",
"dt_probs = dt.predict_proba(X_test1)\n",
"rfc_probs = rfc.predict_proba(X_test1)\n",
"sgd_probs = sgd.predict_proba(X_test1)\n",
"\n",
"# Get the true positive rate and false positive rate for each classifier at different probability thresholds\n",
"lr_fpr, lr_tpr, _ = roc_curve(y_test1, lr_probs[:, 1])\n",
"etc_fpr, etc_tpr, _ = roc_curve(y_test1, etc_probs[:, 1])\n",
"gbm_fpr, gbm_tpr, _ = roc_curve(y_test1, gbm_probs[:, 1])\n",
"knn_fpr, knn_tpr, _ = roc_curve(y_test1, knn_probs[:, 1])\n",
"svm_fpr, svm_tpr, _ = roc_curve(y_test1, svm_probs[:, 1])\n",
"ada_fpr, ada_tpr, _ = roc_curve(y_test1, ada_probs[:, 1])\n",
"dt_fpr, dt_tpr, _ = roc_curve(y_test1, dt_probs[:, 1])\n",
"rfc_fpr, rfc_tpr, _ = roc_curve(y_test1, rfc_probs[:, 1])\n",
"sgd_fpr, sgd_tpr, _ = roc_curve(y_test1, sgd_probs[:, 1])\n",
"\n",
"# Calculate the area under the ROC curve for each classifier\n",
"lr_auc = roc_auc_score(y_test1, lr_probs[:, 1])\n",
"etc_auc = roc_auc_score(y_test1, etc_probs[:, 1])\n",
"gbm_auc = roc_auc_score(y_test1, gbm_probs[:, 1])\n",
"knn_auc = roc_auc_score(y_test1, knn_probs[:, 1])\n",
"svm_auc = roc_auc_score(y_test1, svm_probs[:, 1])\n",
"ada_auc = roc_auc_score(y_test1, ada_probs[:, 1])\n",
"\n",
"dt_auc = roc_auc_score(y_test1, lr_probs[:, 1])\n",
"rfc_auc = roc_auc_score(y_test1, rfc_probs[:, 1])\n",
"sgd_auc = roc_auc_score(y_test1, sgd_probs[:, 1])\n",
"\n",
"\n",
"# Plot the ROC curves\n",
"plt.figure(figsize=(10, 4.7))\n",
"plt.plot(lr_fpr, lr_tpr, label=f'LR (AUC = {lr_auc:.2f})')\n",
"plt.plot(etc_fpr, etc_tpr, label=f'ETC (AUC = {etc_auc:.2f})')\n",
"plt.plot(gbm_fpr, gbm_tpr, label=f'GBM (AUC = {gbm_auc:.2f})')\n",
"\n",
"plt.plot(knn_fpr, knn_tpr, label=f'KNN (AUC = {knn_auc:.2f})')\n",
"plt.plot(svm_fpr, svm_tpr, label=f'SVM (AUC = {svm_auc:.2f})')\n",
"plt.plot(ada_fpr, ada_tpr, label=f'ADA (AUC = {ada_auc:.2f})')\n",
"\n",
"plt.plot(dt_fpr, dt_tpr, label=f'DT (AUC = {dt_auc:.2f})')\n",
"plt.plot(rfc_fpr, rfc_tpr, label=f'RF (AUC = {rfc_auc:.2f})')\n",
"plt.plot(sgd_fpr, sgd_tpr, label=f'SGD (AUC = {sgd_auc:.2f})')\n",
"\n",
"plt.plot([0, 1], [0, 1], linestyle='--', label='Random Guessing')\n",
"plt.xlabel('False Positive Rate')\n",
"plt.ylabel('True Positive Rate')\n",
"plt.title('ROC Curves using SMOTE Oversampling Technique')\n",
"plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e8552fe4",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "ca240ef3",
"metadata": {},
"source": [
"# ENSEMBLE USING STACKING TECHNIQUE ON SMOTED DATA"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "67d9953c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 1.00 1.00 1.00 1492\n",
" 1 1.00 1.00 1.00 1425\n",
"\n",
" accuracy 1.00 2917\n",
" macro avg 1.00 1.00 1.00 2917\n",
"weighted avg 1.00 1.00 1.00 2917\n",
"\n",
"[[1491 1]\n",
" [ 0 1425]]\n",
"Accuracy: 0.999657\n"
]
}
],
"source": [
"from sklearn.model_selection import train_test_split, cross_val_predict\n",
"from sklearn.tree import DecisionTreeClassifier, ExtraTreeClassifier\n",
"from sklearn.ensemble import RandomForestClassifier, StackingClassifier\n",
"from sklearn.pipeline import make_pipeline\n",
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.metrics import accuracy_score\n",
"\n",
"# Load the Stroke Prediction dataset\n",
"#data = pd.read_csv('stroke_data.csv')\n",
"\n",
"\n",
"# Define base classifiers\n",
"dt = DecisionTreeClassifier(random_state=42)\n",
"et = ExtraTreeClassifier(random_state=42)\n",
"rf = RandomForestClassifier(n_estimators=100, random_state=42)\n",
"\n",
"# Define the stacking ensemble\n",
"estimators = [('dt', dt), ('et', et), ('rf', rf)]\n",
"stacked = StackingClassifier(estimators=estimators, final_estimator=RandomForestClassifier(random_state=42))\n",
"\n",
"# Define the pipeline for preprocessing and classification\n",
"pipeline1 = make_pipeline(StandardScaler(), stacked)\n",
"\n",
"# Use cross-validation to fit the stacking ensemble\n",
"stacked_preds = cross_val_predict(pipeline1, X_train1, y_train1, cv=5)\n",
"\n",
"# Evaluate the ensemble on the test set\n",
"pipeline1.fit(X_train1, y_train1)\n",
"stacked_test_preds = pipeline1.predict(X_test1)\n",
"\n",
"print(classification_report(y_test1, stacked_test_preds))\n",
"print(confusion_matrix(y_test1, stacked_test_preds))\n",
"accuracy = accuracy_score(y_test1, stacked_test_preds)\n",
"print('Accuracy: %f' % accuracy)\n"
]
},
{
"cell_type": "markdown",
"id": "a8f9a933",
"metadata": {},
"source": [
"# ENSEMBLE USING HARD VOTING ON SMOTED DATA"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "3f54e692",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 1.00 0.98 0.99 1492\n",
" 1 0.98 1.00 0.99 1425\n",
"\n",
" accuracy 0.99 2917\n",
" macro avg 0.99 0.99 0.99 2917\n",
"weighted avg 0.99 0.99 0.99 2917\n",
"\n",
"[[1460 32]\n",
" [ 0 1425]]\n",
"Accuracy: 0.989030\n"
]
}
],
"source": [
"# Create individual models\n",
"model1 = DecisionTreeClassifier(random_state=42)\n",
"model2 = ExtraTreeClassifier(random_state=42)\n",
"model3 = RandomForestClassifier(n_estimators=100, random_state=42)\n",
"# Create ensemble model with Voting Classifier\n",
"ensemble_model = VotingClassifier(estimators=[('svm', model1), ('dt', model2), ('rf', model3)], voting='hard')\n",
"\n",
"# Fit the ensemble model to the training data\n",
"ensemble_model.fit(X_train1, y_train1)\n",
"\n",
"# Predict on test data using the ensemble model\n",
"y_pred = ensemble_model.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred))\n",
"print(confusion_matrix(y_test1, y_pred))\n",
"accuracy = accuracy_score(y_test1, y_pred)\n",
"print('Accuracy: %f' % accuracy)"
]
},
{
"cell_type": "markdown",
"id": "5e19889e",
"metadata": {},
"source": [
"# ENSEMBLE USING SOFT VOTING ON SMOTED DATA"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "93f7e251",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 1.00 0.98 0.99 1492\n",
" 1 0.98 1.00 0.99 1425\n",
"\n",
" accuracy 0.99 2917\n",
" macro avg 0.99 0.99 0.99 2917\n",
"weighted avg 0.99 0.99 0.99 2917\n",
"\n",
"[[1460 32]\n",
" [ 0 1425]]\n",
"Accuracy: 0.989030\n"
]
}
],
"source": [
"# Create individual models\n",
"model1 = DecisionTreeClassifier(random_state=42)\n",
"model2 = ExtraTreeClassifier(random_state=42)\n",
"model3 = RandomForestClassifier(n_estimators=100, random_state=42)\n",
"# Create ensemble model with Voting Classifier\n",
"ensemble_model_s = VotingClassifier(estimators=[('svm', model1), ('dt', model2), ('rf', model3)], voting='soft')\n",
"\n",
"# Fit the ensemble model to the training data\n",
"ensemble_model_s.fit(X_train1, y_train1)\n",
"\n",
"# Predict on test data using the ensemble model\n",
"y_pred = ensemble_model_s.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred))\n",
"print(confusion_matrix(y_test1, y_pred))\n",
"accuracy = accuracy_score(y_test1, y_pred)\n",
"print('Accuracy: %f' % accuracy)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "07030b7f",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
" #Get the predicted probabilities for each classifier on the test data\n",
"pipeline1_probs = pipeline1.predict_proba(X_test1)\n",
"ensemble_model_s_probs = ensemble_model_s.predict_proba(X_test1)\n",
"#ensemble_model_h_probs = ensemble_model_h.predict_proba(X_test1)\n",
"\n",
"\n",
"# Get the true positive rate and false positive rate for each classifier at different probability thresholds\n",
"pipeline1_fpr, pipeline1_tpr, _ = roc_curve(y_test1, pipeline1_probs[:, 1])\n",
"ensemble_model_s_fpr, ensemble_model_s_tpr, _ = roc_curve(y_test1, ensemble_model_s_probs[:, 1])\n",
"#ensemble_model_h_fpr, ensemble_model_h_tpr, _ = roc_curve(y_test1, ensemble_model_h_probs[:, 1])\n",
"\n",
"\n",
"# Calculate the area under the ROC curve for each classifier\n",
"pipeline1_auc = roc_auc_score(y_test1, pipeline1_probs[:, 1])\n",
"ensemble_model_s_auc = roc_auc_score(y_test1, ensemble_model_s_probs[:, 1])\n",
"#ensemble_model_h_auc = roc_auc_score(y_test1, ensemble_model_h_probs[:, 1])\n",
"\n",
"\n",
"\n",
"# Plot the ROC curves\n",
"plt.figure(figsize=(8, 4))\n",
"plt.plot(pipeline1_fpr, pipeline1_tpr, label=f'Ensemble Stacking (AUC = {pipeline1_auc:.2f})')\n",
"plt.plot(ensemble_model_s_fpr, ensemble_model_s_tpr, label=f'Ensemble Voting Classifier (AUC = {ensemble_model_s_auc:.2f})')\n",
"#plt.plot(ensemble_model_h_fpr, ensemble_model_h_tpr, label=f'H (AUC = {ensemble_model_h_auc:.2f})')\n",
"\n",
"plt.plot([0, 1], [0, 1], linestyle='--', label='Random Guessing')\n",
"plt.xlabel('False Positive Rate')\n",
"plt.ylabel('True Positive Rate')\n",
"plt.title('ROC Curves using SMOTE Oversampling Technique')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "1dab3790",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Stacked ensemble accuracy (train): 0.9995591476855253\n",
"Stacked ensemble accuracy (test): 0.9996571820363387\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"from sklearn.datasets import load_iris\n",
"from sklearn.model_selection import train_test_split, learning_curve, cross_val_predict\n",
"from sklearn.tree import DecisionTreeClassifier, ExtraTreeClassifier\n",
"from sklearn.ensemble import RandomForestClassifier, StackingClassifier\n",
"from sklearn.pipeline import make_pipeline\n",
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.metrics import accuracy_score\n",
"\n",
"\n",
"# Split the data into training and testing sets\n",
"\n",
"# Define base classifiers\n",
"dt = DecisionTreeClassifier(random_state=42)\n",
"et = ExtraTreeClassifier(random_state=42)\n",
"rf = RandomForestClassifier(n_estimators=100, random_state=42)\n",
"\n",
"# Define the stacking ensemble\n",
"estimators = [('dt', dt), ('et', et), ('rf', rf)]\n",
"stacked = StackingClassifier(estimators=estimators, final_estimator=RandomForestClassifier(random_state=42))\n",
"\n",
"# Define the pipeline for preprocessing and classification\n",
"pipeline = make_pipeline(StandardScaler(), stacked)\n",
"\n",
"# Use cross-validation to fit the stacking ensemble\n",
"stacked_preds = cross_val_predict(pipeline, X_train1, y_train1, cv=5)\n",
"\n",
"# Evaluate the ensemble on the test set\n",
"pipeline.fit(X_train1, y_train1)\n",
"stacked_test_preds = pipeline.predict(X_test1)\n",
"\n",
"# Print the training and testing accuracy\n",
"train_accuracy = accuracy_score(y_train1, stacked_preds)\n",
"test_accuracy = accuracy_score(y_test1, stacked_test_preds)\n",
"print(\"Stacked ensemble accuracy (train):\", train_accuracy)\n",
"print(\"Stacked ensemble accuracy (test):\", test_accuracy)\n",
"\n",
"# Plot the learning curves\n",
"train_sizes, train_scores, test_scores = learning_curve(pipeline, X_train1, y_train1, cv=5, train_sizes=np.linspace(0.1, 1.0, 10), scoring='accuracy')\n",
"train_mean = np.mean(train_scores, axis=1)\n",
"train_std = np.std(train_scores, axis=1)\n",
"test_mean = np.mean(test_scores, axis=1)\n",
"test_std = np.std(test_scores, axis=1)\n",
"plt.figure(figsize=(7, 4))\n",
"plt.plot(train_sizes, train_mean, color='blue', marker='o', markersize=5, label='Training accuracy')\n",
"plt.fill_between(train_sizes, train_mean + train_std, train_mean - train_std, alpha=0.15, color='blue')\n",
"plt.plot(train_sizes, test_mean, color='green', linestyle='--', marker='s', markersize=5, label='Testing accuracy')\n",
"plt.fill_between(train_sizes, test_mean + test_std, test_mean - test_std, alpha=0.15, color='green')\n",
"plt.grid()\n",
"plt.xlabel(' Training samples')\n",
"plt.ylabel('Accuracy')\n",
"plt.legend(loc='lower right')\n",
"plt.ylim([0.88, 1.02])\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2c7797be",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "8bbb8e6c",
"metadata": {},
"source": [
"# SINGLE MODELS USING ADASYN DATA"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "a2347135",
"metadata": {},
"outputs": [],
"source": [
"from imblearn.over_sampling import SMOTE, ADASYN\n",
"adasyn = ADASYN(random_state=2)\n",
"x_train_res, y_train_res = adasyn.fit_resample(X, y.ravel())\n",
"X_train1, X_test1, y_train1, y_test1 = train_test_split(x_train_res, y_train_res, test_size=0.3)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "0d2ebf37",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"LR\n",
" precision recall f1-score support\n",
"\n",
" 0 0.81 0.74 0.77 1491\n",
" 1 0.75 0.82 0.79 1431\n",
"\n",
" accuracy 0.78 2922\n",
" macro avg 0.78 0.78 0.78 2922\n",
"weighted avg 0.78 0.78 0.78 2922\n",
"\n",
"[[1097 394]\n",
" [ 251 1180]]\n",
"Accuracy: 0.779261\n",
"Execution time: 0.22440218925476074 secs\n",
"ETC\n",
" precision recall f1-score support\n",
"\n",
" 0 0.96 0.92 0.94 1491\n",
" 1 0.92 0.96 0.94 1431\n",
"\n",
" accuracy 0.94 2922\n",
" macro avg 0.94 0.94 0.94 2922\n",
"weighted avg 0.94 0.94 0.94 2922\n",
"\n",
"[[1379 112]\n",
" [ 58 1373]]\n",
"Accuracy: 0.941821\n",
"Execution time: 0.09973382949829102 secs\n",
"GBM\n",
" precision recall f1-score support\n",
"\n",
" 0 0.94 0.92 0.93 1491\n",
" 1 0.92 0.94 0.92 1431\n",
"\n",
" accuracy 0.93 2922\n",
" macro avg 0.93 0.93 0.93 2922\n",
"weighted avg 0.93 0.93 0.93 2922\n",
"\n",
"[[1367 124]\n",
" [ 93 1338]]\n",
"Accuracy: 0.925736\n",
"Execution time: 8.034685850143433 secs\n",
"KNN\n",
" precision recall f1-score support\n",
"\n",
" 0 0.99 0.85 0.92 1491\n",
" 1 0.87 0.99 0.93 1431\n",
"\n",
" accuracy 0.92 2922\n",
" macro avg 0.93 0.92 0.92 2922\n",
"weighted avg 0.93 0.92 0.92 2922\n",
"\n",
"[[1270 221]\n",
" [ 8 1423]]\n",
"Accuracy: 0.921629\n",
"Execution time: 0.5315847396850586 secs\n",
"SVC\n",
" precision recall f1-score support\n",
"\n",
" 0 0.66 0.64 0.65 1491\n",
" 1 0.64 0.65 0.64 1431\n",
"\n",
" accuracy 0.65 2922\n",
" macro avg 0.65 0.65 0.65 2922\n",
"weighted avg 0.65 0.65 0.65 2922\n",
"\n",
"[[958 533]\n",
" [503 928]]\n",
"Accuracy: 0.645448\n",
"Execution time: 8.783185720443726 secs\n",
"ADA\n",
" precision recall f1-score support\n",
"\n",
" 0 0.90 0.87 0.88 1491\n",
" 1 0.87 0.89 0.88 1431\n",
"\n",
" accuracy 0.88 2922\n",
" macro avg 0.88 0.88 0.88 2922\n",
"weighted avg 0.88 0.88 0.88 2922\n",
"\n",
"[[1299 192]\n",
" [ 151 1280]]\n",
"Accuracy: 0.882615\n",
"Execution time: 1.1429829597473145 secs\n",
"DT\n",
" precision recall f1-score support\n",
"\n",
" 0 0.93 0.91 0.92 1491\n",
" 1 0.91 0.93 0.92 1431\n",
"\n",
" accuracy 0.92 2922\n",
" macro avg 0.92 0.92 0.92 2922\n",
"weighted avg 0.92 0.92 0.92 2922\n",
"\n",
"[[1362 129]\n",
" [ 99 1332]]\n",
"Accuracy: 0.921971\n",
"Execution time: 0.07799005508422852 secs\n",
"SGD\n",
" precision recall f1-score support\n",
"\n",
" 0 0.80 0.62 0.70 1491\n",
" 1 0.68 0.84 0.75 1431\n",
"\n",
" accuracy 0.73 2922\n",
" macro avg 0.74 0.73 0.72 2922\n",
"weighted avg 0.74 0.73 0.72 2922\n",
"\n",
"[[ 928 563]\n",
" [ 235 1196]]\n",
"Accuracy: 0.726899\n",
"Execution time: 0.026731252670288086 secs\n",
"RF\n",
" precision recall f1-score support\n",
"\n",
" 0 0.96 0.92 0.94 1491\n",
" 1 0.92 0.96 0.94 1431\n",
"\n",
" accuracy 0.94 2922\n",
" macro avg 0.94 0.94 0.94 2922\n",
"weighted avg 0.94 0.94 0.94 2922\n",
"\n",
"[[1371 120]\n",
" [ 64 1367]]\n",
"Accuracy: 0.937029\n",
"Execution time: 0.12267136573791504 secs\n"
]
}
],
"source": [
"\n",
"#machine learning models\n",
"\n",
"##########2\n",
"start_time = time.time()\n",
"from sklearn.linear_model import LogisticRegression\n",
"print(\"LR\")\n",
"lr = LogisticRegression(random_state=300, solver='newton-cg',multi_class='multinomial',C=1.0)\n",
"lr.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = lr.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"#########3\n",
"start_time = time.time()\n",
"from sklearn.ensemble import ExtraTreesClassifier\n",
"print(\"ETC\")\n",
"etc = ExtraTreesClassifier(n_estimators=10,random_state=150,max_samples=0.5, max_depth=50,bootstrap=True)\n",
"etc.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = etc.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"#######4\n",
"import time # this is an inbuilt library in Python\n",
"start_time = time.time()\n",
"from sklearn.ensemble import GradientBoostingClassifier\n",
"print(\"GBM\")\n",
"gbm = GradientBoostingClassifier(n_estimators=100, random_state=50, max_depth=100)\n",
"gbm.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = gbm.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"########5\n",
"import time # this is an inbuilt library in Python\n",
"start_time = time.time()\n",
"from sklearn.neighbors import KNeighborsClassifier\n",
"print(\"KNN\")\n",
"knn = KNeighborsClassifier(n_neighbors=3)\n",
"knn.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = knn.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"#######6\n",
"start_time = time.time()\n",
"from sklearn.svm import SVC\n",
"print(\"SVC\")\n",
"svm = SVC(kernel='sigmoid', C=2.0, random_state=100,probability=True)\n",
"svm.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = svm.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"########7\n",
"start_time = time.time()\n",
"from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier\n",
"from sklearn.svm import SVC\n",
"print(\"ADA\")\n",
"ada = AdaBoostClassifier(n_estimators=100, random_state=50)\n",
"ada.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = ada.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"########8\n",
"start_time = time.time()\n",
"from sklearn.tree import DecisionTreeClassifier\n",
"dt = DecisionTreeClassifier(random_state=50, max_depth=100)\n",
"print(\"DT\")\n",
"dt.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = dt.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"\n",
"###9\n",
"start_time = time.time()\n",
"from sklearn.linear_model import SGDClassifier\n",
"sgd = SGDClassifier(loss=\"modified_huber\", penalty=\"l2\", max_iter=5)\n",
"print(\"SGD\")\n",
"sgd.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = sgd.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n",
"\n",
"\n",
"#########1\n",
"start_time = time.time()\n",
"from sklearn.ensemble import RandomForestClassifier, VotingClassifier\n",
"print(\"RF\")\n",
"rfc = RandomForestClassifier(n_estimators=10,random_state=150,max_samples=0.5, max_depth=50) \n",
"rfc.fit(X_train1, y_train1)\n",
"# calculate accuracy of class predictions\n",
"y_pred_class = rfc.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred_class))\n",
"print(confusion_matrix(y_test1, y_pred_class))\n",
"accuracy = accuracy_score(y_test1, y_pred_class)\n",
"print('Accuracy: %f' % accuracy)\n",
"end_time = time.time()\n",
"print(\"Execution time: \", end_time - start_time,\"secs\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d9b2113c",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 29,
"id": "6b7f4784",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
" #Get the predicted probabilities for each classifier on the test data\n",
"lr_probs = lr.predict_proba(X_test1)\n",
"etc_probs = etc.predict_proba(X_test1)\n",
"gbm_probs = gbm.predict_proba(X_test1)\n",
"knn_probs = knn.predict_proba(X_test1)\n",
"svm_probs = svm.predict_proba(X_test1)\n",
"ada_probs = ada.predict_proba(X_test1)\n",
"dt_probs = dt.predict_proba(X_test1)\n",
"rfc_probs = rfc.predict_proba(X_test1)\n",
"sgd_probs = sgd.predict_proba(X_test1)\n",
"\n",
"# Get the true positive rate and false positive rate for each classifier at different probability thresholds\n",
"lr_fpr, lr_tpr, _ = roc_curve(y_test1, lr_probs[:, 1])\n",
"etc_fpr, etc_tpr, _ = roc_curve(y_test1, etc_probs[:, 1])\n",
"gbm_fpr, gbm_tpr, _ = roc_curve(y_test1, gbm_probs[:, 1])\n",
"knn_fpr, knn_tpr, _ = roc_curve(y_test1, knn_probs[:, 1])\n",
"svm_fpr, svm_tpr, _ = roc_curve(y_test1, svm_probs[:, 1])\n",
"ada_fpr, ada_tpr, _ = roc_curve(y_test1, ada_probs[:, 1])\n",
"dt_fpr, dt_tpr, _ = roc_curve(y_test1, dt_probs[:, 1])\n",
"rfc_fpr, rfc_tpr, _ = roc_curve(y_test1, rfc_probs[:, 1])\n",
"sgd_fpr, sgd_tpr, _ = roc_curve(y_test1, sgd_probs[:, 1])\n",
"\n",
"# Calculate the area under the ROC curve for each classifier\n",
"lr_auc = roc_auc_score(y_test1, lr_probs[:, 1])\n",
"etc_auc = roc_auc_score(y_test1, etc_probs[:, 1])\n",
"gbm_auc = roc_auc_score(y_test1, gbm_probs[:, 1])\n",
"knn_auc = roc_auc_score(y_test1, knn_probs[:, 1])\n",
"svm_auc = roc_auc_score(y_test1, svm_probs[:, 1])\n",
"ada_auc = roc_auc_score(y_test1, ada_probs[:, 1])\n",
"\n",
"dt_auc = roc_auc_score(y_test1, lr_probs[:, 1])\n",
"rfc_auc = roc_auc_score(y_test1, rfc_probs[:, 1])\n",
"sgd_auc = roc_auc_score(y_test1, sgd_probs[:, 1])\n",
"\n",
"\n",
"# Plot the ROC curves\n",
"plt.figure(figsize=(10, 4.7))\n",
"plt.plot(lr_fpr, lr_tpr, label=f'LR (AUC = {lr_auc:.2f})')\n",
"plt.plot(etc_fpr, etc_tpr, label=f'ETC (AUC = {etc_auc:.2f})')\n",
"plt.plot(gbm_fpr, gbm_tpr, label=f'GBM (AUC = {gbm_auc:.2f})')\n",
"\n",
"plt.plot(knn_fpr, knn_tpr, label=f'KNN (AUC = {knn_auc:.2f})')\n",
"plt.plot(svm_fpr, svm_tpr, label=f'SVM (AUC = {svm_auc:.2f})')\n",
"plt.plot(ada_fpr, ada_tpr, label=f'ADA (AUC = {ada_auc:.2f})')\n",
"\n",
"plt.plot(dt_fpr, dt_tpr, label=f'DT (AUC = {dt_auc:.2f})')\n",
"plt.plot(rfc_fpr, rfc_tpr, label=f'RF (AUC = {rfc_auc:.2f})')\n",
"plt.plot(sgd_fpr, sgd_tpr, label=f'SGD (AUC = {sgd_auc:.2f})')\n",
"\n",
"plt.plot([0, 1], [0, 1], linestyle='--', label='Random Guessing')\n",
"plt.xlabel('False Positive Rate')\n",
"plt.ylabel('True Positive Rate')\n",
"plt.title('ROC Curves using ADASYN Oversampling Technique')\n",
"plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "114e0076",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "ece2a201",
"metadata": {},
"source": [
"# ENSEMBEL STACKING USING ADASYN DATA"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "374a7502",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.97 0.96 0.96 1491\n",
" 1 0.96 0.97 0.96 1431\n",
"\n",
" accuracy 0.96 2922\n",
" macro avg 0.96 0.96 0.96 2922\n",
"weighted avg 0.96 0.96 0.96 2922\n",
"\n",
"[[1433 58]\n",
" [ 49 1382]]\n",
"Accuracy: 0.963381\n"
]
}
],
"source": [
"from sklearn.model_selection import train_test_split, cross_val_predict\n",
"from sklearn.tree import DecisionTreeClassifier, ExtraTreeClassifier\n",
"from sklearn.ensemble import RandomForestClassifier, StackingClassifier\n",
"from sklearn.pipeline import make_pipeline\n",
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.metrics import accuracy_score\n",
"\n",
"# Load the Stroke Prediction dataset\n",
"#data = pd.read_csv('stroke_data.csv')\n",
"\n",
"\n",
"# Define base classifiers\n",
"dt = DecisionTreeClassifier(random_state=42)\n",
"et = ExtraTreeClassifier(random_state=42)\n",
"rf = RandomForestClassifier(n_estimators=100, random_state=42)\n",
"\n",
"# Define the stacking ensemble\n",
"estimators = [('dt', dt), ('et', et), ('rf', rf)]\n",
"stacked = StackingClassifier(estimators=estimators, final_estimator=RandomForestClassifier(random_state=42))\n",
"\n",
"# Define the pipeline for preprocessing and classification\n",
"pipeline1 = make_pipeline(StandardScaler(), stacked)\n",
"\n",
"# Use cross-validation to fit the stacking ensemble\n",
"stacked_preds = cross_val_predict(pipeline1, X_train1, y_train1, cv=5)\n",
"\n",
"# Evaluate the ensemble on the test set\n",
"pipeline1.fit(X_train1, y_train1)\n",
"stacked_test_preds = pipeline1.predict(X_test1)\n",
"\n",
"print(classification_report(y_test1, stacked_test_preds))\n",
"print(confusion_matrix(y_test1, stacked_test_preds))\n",
"accuracy = accuracy_score(y_test1, stacked_test_preds)\n",
"print('Accuracy: %f' % accuracy)\n"
]
},
{
"cell_type": "markdown",
"id": "7ebe0a86",
"metadata": {},
"source": [
"# ENSEMBLE USING HARD VOTING ON ADASYN DATA"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "739c5c7d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.97 0.95 0.96 1491\n",
" 1 0.95 0.97 0.96 1431\n",
"\n",
" accuracy 0.96 2922\n",
" macro avg 0.96 0.96 0.96 2922\n",
"weighted avg 0.96 0.96 0.96 2922\n",
"\n",
"[[1415 76]\n",
" [ 44 1387]]\n",
"Accuracy: 0.958932\n"
]
}
],
"source": [
"# Create individual models\n",
"model1 = DecisionTreeClassifier(random_state=42)\n",
"model2 = ExtraTreeClassifier(random_state=42)\n",
"model3 = RandomForestClassifier(n_estimators=100, random_state=42)\n",
"# Create ensemble model with Voting Classifier\n",
"ensemble_model = VotingClassifier(estimators=[('svm', model1), ('dt', model2), ('rf', model3)], voting='hard')\n",
"\n",
"# Fit the ensemble model to the training data\n",
"ensemble_model.fit(X_train1, y_train1)\n",
"\n",
"# Predict on test data using the ensemble model\n",
"y_pred = ensemble_model.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred))\n",
"print(confusion_matrix(y_test1, y_pred))\n",
"accuracy = accuracy_score(y_test1, y_pred)\n",
"print('Accuracy: %f' % accuracy)"
]
},
{
"cell_type": "markdown",
"id": "6d7f657a",
"metadata": {},
"source": [
"# ENSEMBLE USING SOFT VOTING ON ADASYN DATA"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "d587be84",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.97 0.95 0.96 1491\n",
" 1 0.95 0.97 0.96 1431\n",
"\n",
" accuracy 0.96 2922\n",
" macro avg 0.96 0.96 0.96 2922\n",
"weighted avg 0.96 0.96 0.96 2922\n",
"\n",
"[[1415 76]\n",
" [ 44 1387]]\n",
"Accuracy: 0.958932\n"
]
}
],
"source": [
"# Create individual models\n",
"model1 = DecisionTreeClassifier(random_state=42)\n",
"model2 = ExtraTreeClassifier(random_state=42)\n",
"model3 = RandomForestClassifier(n_estimators=100, random_state=42)\n",
"# Create ensemble model with Voting Classifier\n",
"ensemble_model_s = VotingClassifier(estimators=[('svm', model1), ('dt', model2), ('rf', model3)], voting='soft')\n",
"\n",
"# Fit the ensemble model to the training data\n",
"ensemble_model_s.fit(X_train1, y_train1)\n",
"\n",
"# Predict on test data using the ensemble model\n",
"y_pred = ensemble_model_s.predict(X_test1)\n",
"print(classification_report(y_test1, y_pred))\n",
"print(confusion_matrix(y_test1, y_pred))\n",
"accuracy = accuracy_score(y_test1, y_pred)\n",
"print('Accuracy: %f' % accuracy)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "0dfb2a66",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
" #Get the predicted probabilities for each classifier on the test data\n",
"pipeline1_probs = pipeline1.predict_proba(X_test1)\n",
"ensemble_model_s_probs = ensemble_model_s.predict_proba(X_test1)\n",
"#ensemble_model_h_probs = ensemble_model_h.predict_proba(X_test1)\n",
"\n",
"\n",
"# Get the true positive rate and false positive rate for each classifier at different probability thresholds\n",
"pipeline1_fpr, pipeline1_tpr, _ = roc_curve(y_test1, pipeline1_probs[:, 1])\n",
"ensemble_model_s_fpr, ensemble_model_s_tpr, _ = roc_curve(y_test1, ensemble_model_s_probs[:, 1])\n",
"#ensemble_model_h_fpr, ensemble_model_h_tpr, _ = roc_curve(y_test1, ensemble_model_h_probs[:, 1])\n",
"\n",
"\n",
"# Calculate the area under the ROC curve for each classifier\n",
"pipeline1_auc = roc_auc_score(y_test1, pipeline1_probs[:, 1])\n",
"ensemble_model_s_auc = roc_auc_score(y_test1, ensemble_model_s_probs[:, 1])\n",
"#ensemble_model_h_auc = roc_auc_score(y_test1, ensemble_model_h_probs[:, 1])\n",
"\n",
"\n",
"\n",
"# Plot the ROC curves\n",
"plt.figure(figsize=(8, 4))\n",
"plt.plot(pipeline1_fpr, pipeline1_tpr, label=f'Ensemble Stacking (AUC = {pipeline1_auc:.2f})')\n",
"plt.plot(ensemble_model_s_fpr, ensemble_model_s_tpr, label=f'Ensemble Voting Classifier (AUC = {ensemble_model_s_auc:.2f})')\n",
"#plt.plot(ensemble_model_h_fpr, ensemble_model_h_tpr, label=f'H (AUC = {ensemble_model_h_auc:.2f})')\n",
"\n",
"plt.plot([0, 1], [0, 1], linestyle='--', label='Random Guessing')\n",
"plt.xlabel('False Positive Rate')\n",
"plt.ylabel('True Positive Rate')\n",
"plt.title('ROC Curves using ADASYN Oversampling Technique')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "38deb45e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Stacked ensemble accuracy (train): 0.9527720739219713\n",
"Stacked ensemble accuracy (test): 0.9633812457221081\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"from sklearn.datasets import load_iris\n",
"from sklearn.model_selection import train_test_split, learning_curve, cross_val_predict\n",
"from sklearn.tree import DecisionTreeClassifier, ExtraTreeClassifier\n",
"from sklearn.ensemble import RandomForestClassifier, StackingClassifier\n",
"from sklearn.pipeline import make_pipeline\n",
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.metrics import accuracy_score\n",
"\n",
"\n",
"# Split the data into training and testing sets\n",
"\n",
"# Define base classifiers\n",
"dt = DecisionTreeClassifier(random_state=42)\n",
"et = ExtraTreeClassifier(random_state=42)\n",
"rf = RandomForestClassifier(n_estimators=100, random_state=42)\n",
"\n",
"# Define the stacking ensemble\n",
"estimators = [('dt', dt), ('et', et), ('rf', rf)]\n",
"stacked = StackingClassifier(estimators=estimators, final_estimator=RandomForestClassifier(random_state=42))\n",
"\n",
"# Define the pipeline for preprocessing and classification\n",
"pipeline = make_pipeline(StandardScaler(), stacked)\n",
"\n",
"# Use cross-validation to fit the stacking ensemble\n",
"stacked_preds = cross_val_predict(pipeline, X_train1, y_train1, cv=5)\n",
"\n",
"# Evaluate the ensemble on the test set\n",
"pipeline.fit(X_train1, y_train1)\n",
"stacked_test_preds = pipeline.predict(X_test1)\n",
"\n",
"# Print the training and testing accuracy\n",
"train_accuracy = accuracy_score(y_train1, stacked_preds)\n",
"test_accuracy = accuracy_score(y_test1, stacked_test_preds)\n",
"print(\"Stacked ensemble accuracy (train):\", train_accuracy)\n",
"print(\"Stacked ensemble accuracy (test):\", test_accuracy)\n",
"\n",
"# Plot the learning curves\n",
"train_sizes, train_scores, test_scores = learning_curve(pipeline, X_train1, y_train1, cv=5, train_sizes=np.linspace(0.1, 1.0, 10), scoring='accuracy')\n",
"train_mean = np.mean(train_scores, axis=1)\n",
"train_std = np.std(train_scores, axis=1)\n",
"test_mean = np.mean(test_scores, axis=1)\n",
"test_std = np.std(test_scores, axis=1)\n",
"plt.figure(figsize=(7, 4))\n",
"plt.plot(train_sizes, train_mean, color='blue', marker='o', markersize=5, label='Training accuracy')\n",
"plt.fill_between(train_sizes, train_mean + train_std, train_mean - train_std, alpha=0.15, color='blue')\n",
"plt.plot(train_sizes, test_mean, color='green', linestyle='--', marker='s', markersize=5, label='Testing accuracy')\n",
"plt.fill_between(train_sizes, test_mean + test_std, test_mean - test_std, alpha=0.15, color='green')\n",
"plt.grid()\n",
"plt.xlabel(' Training samples')\n",
"plt.ylabel('Accuracy')\n",
"plt.legend(loc='lower right')\n",
"plt.ylim([0.88, 1.02])\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f8dae853",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "d0fa6bbf",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "b47983f7",
"metadata": {},
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},
{
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"id": "dd52e02a",
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},
{
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"id": "5de3ceed",
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},
{
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"id": "1b6959ff",
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{
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"execution_count": null,
"id": "250a039d",
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},
{
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"execution_count": null,
"id": "ec7c0a0c",
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},
{
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"execution_count": null,
"id": "ded41ad3",
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},
{
"cell_type": "code",
"execution_count": null,
"id": "02a6ba74",
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},
{
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"execution_count": null,
"id": "6344a395",
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},
{
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"id": "b73f841f",
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},
{
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"execution_count": null,
"id": "890ace16",
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},
{
"cell_type": "code",
"execution_count": null,
"id": "5edfdee7",
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},
{
"cell_type": "code",
"execution_count": null,
"id": "90615725",
"metadata": {},
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"source": []
},
{
"cell_type": "code",
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"id": "59a5dddc",
"metadata": {},
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},
{
"cell_type": "code",
"execution_count": null,
"id": "1666e7ac",
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