| import joblib | |
| from sklearn.linear_model import LogisticRegression | |
| import numpy as np | |
| # Training data (toy example) | |
| X = np.array([[0], [1], [2], [3], [4], [5]]) | |
| y = np.array([0, 1, 0, 1, 0, 1]) # 0 = even, 1 = odd | |
| model = LogisticRegression() | |
| model.fit(X, y) | |
| # Save model | |
| joblib.dump(model, "model.joblib") | |
| print("Model trained and saved as model.joblib") |