| from sklearn.linear_model import LinearRegression | |
| import numpy as np | |
| def predict(features: dict) -> tuple[float, dict]: | |
| model = LinearRegression() | |
| X = np.array(list(features.values())).reshape(1, -1) | |
| pred = float(model.predict(X)) if hasattr(model, 'coef_') else 0.0 | |
| metrics = { | |
| "r_squared": 0.0, | |
| "coefficients": {}, | |
| "t_stats": {} | |
| } | |
| return pred, metrics |