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app.py
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app.py
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from flask import Flask, render_template, request
import pandas as pd
import joblib
app = Flask(__name__)
# Load the saved Linear Regression model
model = joblib.load(r'model.pkl')
@app.route('/')
def index():
return render_template('index.html')
@app.route('/predict', methods=['POST'])
def predict():
if request.method == 'POST':
# Get user input from the form
Mat = int(request.form['Mat'])
NO = int(request.form['NO'])
Runs = int(request.form['Runs'])
BF = int(request.form['BF'])
SR = float(request.form['SR'])
HS = int(request.form['HS'])
Centuries = int(request.form['100'])
Fifties = int(request.form['50'])
# Create a DataFrame with user input values
user_data = pd.DataFrame([[Mat, NO, Runs, BF, SR, HS, Centuries, Fifties]], columns=[
'Mat', 'NO', 'Runs', 'BF', 'SR', 'HS', '100', '50'])
# Make prediction using the loaded model
user_prediction = model.predict(user_data)
return render_template('index.html', prediction=user_prediction[0])
if __name__ == '__main__':
app.run(debug=True)