├── LICENSE
├── README.md
└── Regression_House Pricing.ipynb Analysis


/LICENSE:
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 1 | MIT License
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 3 | Copyright (c) 2023 mahdieslaminet
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 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
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/README.md:
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1 | # MachineLearningProjects


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/Regression_House Pricing.ipynb Analysis:
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 1 | import numpy as np
 2 | import matplotlib.pyplot as plt
 3 | from sklearn.linear_model import LinearRegression
 4 | from sklearn.preprocessing import PolynomialFeatures
 5 | from sklearn.metrics import mean_squared_error, r2_score
 6 | 
 7 | # داده‌ها (اندازه خانه و قیمت آن)
 8 | sizes = np.array([500, 750, 1000, 1250, 1500, 1750, 2000, 2250, 2500]).reshape(-1, 1)
 9 | prices = np.array([150, 220, 250, 270, 290, 310, 320, 330, 340])
10 | 
11 | # رگرسیون خطی
12 | linear_model = LinearRegression()
13 | linear_model.fit(sizes, prices)
14 | linear_predictions = linear_model.predict(sizes)
15 | 
16 | # رگرسیون درجه دوم
17 | poly = PolynomialFeatures(degree=2)
18 | sizes_poly = poly.fit_transform(sizes)
19 | poly_model = LinearRegression()
20 | poly_model.fit(sizes_poly, prices)
21 | poly_predictions = poly_model.predict(sizes_poly)
22 | 
23 | # ارزیابی مدل‌ها
24 | linear_mse = mean_squared_error(prices, linear_predictions)
25 | linear_r2 = r2_score(prices, linear_predictions)
26 | poly_mse = mean_squared_error(prices, poly_predictions)
27 | poly_r2 = r2_score(prices, poly_predictions)
28 | 
29 | # نمایش نتایج
30 | print("Linear Regression:\n")
31 | print(f"MSE: {linear_mse:.2f}, R2: {linear_r2:.2f}\n")
32 | print("Polynomial Regression (Degree 2):\n")
33 | print(f"MSE: {poly_mse:.2f}, R2: {poly_r2:.2f}\n")
34 | 
35 | # مصورسازی
36 | plt.figure(figsize=(10, 6))
37 | plt.scatter(sizes, prices, color='red', label='Actual Data')
38 | plt.plot(sizes, linear_predictions, color='blue', label='Linear Regression')
39 | plt.plot(sizes, poly_predictions, color='green', label='Polynomial Regression (Degree 2)')
40 | plt.title("House Pricing: Linear vs Polynomial Regression")
41 | plt.xlabel("Size (sq ft)")
42 | plt.ylabel("Price (1000$)")
43 | plt.legend()
44 | plt.grid(True)
45 | plt.show()
46 | 


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