(self, model: BaseEstimator, X_test: np.ndarray,
y_test: np.ndarray)
| 129 | |
| 130 | |
| 131 | def evaluate_model(self, model: BaseEstimator, X_test: np.ndarray, |
| 132 | y_test: np.ndarray) -> Dict[str, float]: |
| 133 | |
| 134 | y_pred = model.predict(X_test) |
| 135 | return { |
| 136 | 'accuracy': accuracy_score(y_test, y_pred), |
| 137 | 'precision': precision_score(y_test, y_pred, average='weighted'), |
| 138 | 'recall': recall_score(y_test, y_pred, average='weighted'), |
| 139 | 'f1': f1_score(y_test, y_pred, average='weighted') |
| 140 | } |
| 141 | |
| 142 | class ModelExplainer: |
| 143 |