# THIS TEST IS BROKEN!! >>> xgboost(np.array([[5.1, 3.6, 1.4, 0.2]]), np.array([0])) XGBClassifier(base_score=0.5, booster='gbtree', callbacks=None, colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1, early_stopping_rounds=None, enable_categorica
(features: np.ndarray, target: np.ndarray)
| 22 | |
| 23 | |
| 24 | def xgboost(features: np.ndarray, target: np.ndarray) -> XGBClassifier: |
| 25 | """ |
| 26 | # THIS TEST IS BROKEN!! >>> xgboost(np.array([[5.1, 3.6, 1.4, 0.2]]), np.array([0])) |
| 27 | XGBClassifier(base_score=0.5, booster='gbtree', callbacks=None, |
| 28 | colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1, |
| 29 | early_stopping_rounds=None, enable_categorical=False, |
| 30 | eval_metric=None, gamma=0, gpu_id=-1, grow_policy='depthwise', |
| 31 | importance_type=None, interaction_constraints='', |
| 32 | learning_rate=0.300000012, max_bin=256, max_cat_to_onehot=4, |
| 33 | max_delta_step=0, max_depth=6, max_leaves=0, min_child_weight=1, |
| 34 | missing=nan, monotone_constraints='()', n_estimators=100, |
| 35 | n_jobs=0, num_parallel_tree=1, predictor='auto', random_state=0, |
| 36 | reg_alpha=0, reg_lambda=1, ...) |
| 37 | """ |
| 38 | classifier = XGBClassifier() |
| 39 | classifier.fit(features, target) |
| 40 | return classifier |
| 41 | |
| 42 | |
| 43 | def main() -> None: |