| # Price-Predictor- | |
| from sklearn.linear_model import LinearRegression | |
| import numpy as np | |
| x = np.array([[1500,3,2],[2000,4,3],[1200,2,3],[1800,3,2],[2500,4,3]]) | |
| y = np.array([250000,350000,200000,400000]) | |
| model = LinearRegression() | |
| model.fit(x,y) | |
| x_new = np.array([[1600,3,2],[2200,4,2]]) | |
| predictions = model.predict(x_new) | |
| for i, pred in enumerate(predictions): | |
| print(f"predicted price for house {i+1}: ${pred:.2f}") | |