model.py 文件源码

def xgb150opt(df_cell_train_feats, y_train, df_cell_test_feats):
    def prepare_feats(df):
        return df.drop(['time'], axis=1)
    logging.info("train xgb150opt model")
    clf = xgb.XGBClassifier(n_estimators=150, learning_rate=0.1, max_depth=3, min_child_weight=3, subsample=0.667, colsample_bytree=1)
    clf.fit(prepare_feats(df_cell_train_feats), y_train)
    y_test_pred = clf.predict_proba(prepare_feats(df_cell_test_feats))
    return y_test_pred