xgboost - hyperopt 结果超出了我的 hp.choice 限制，为什么？ (XGBoost)

Question

我遇到了一个奇怪的问题:
我通过 hyperopt 定义了我的 XGB 超参数 'max_depth'

hp.choice('max_depth',range(2,20))

但我得到了 'max_depth' = 0 或 1 结果，这不在 [2,20) 限制之内。为什么？我错过了什么吗？谢谢。

错误结果:

{'colsample_bytree': 0.18, 'learning_rate': 0.05, 'max_depth': 1, 'reg_alpha': 3.44, 'reg_lambda': 0.92}

{'colsample_bytree': 0.41, 'learning_rate': 0.09, 'max_depth': 0, 'reg_alpha': 0.14, 'reg_lambda': 3.53}

{'colsample_bytree': 0.71, 'learning_rate': 0.17, 'max_depth': 0, 'reg_alpha': 2.21, 'reg_lambda': 2.82}

def xgb_classifier_tune(params):
    obj='binary:logistic' if class_nums==2 else 'multi:softmax'
    random.seed(time.time())
    xgb_model=xgb.XGBClassifier(
            max_depth=params['max_depth'],
            colsample_bytree=params['colsample_bytree'],
            learning_rate=params['learning_rate'],
            reg_alpha=params['reg_alpha'],
            reg_lambda=params['reg_lambda'],
            objective=obj,
            n_estimators=100000,
            random_state=random.randint(0,99999),
            n_jobs=-1)

    if params['max_depth']<2:
        return {'loss':999.999,'status': STATUS_FAIL,'info':[0,0,0,{}]}
    xgb_model.fit(tune_train_x,tune_train_y,eval_set=[(tune_valid_x,tune_valid_y)],verbose=1,early_stopping_rounds=100) #verbose: 0 (silent), 1 (warning), 2 (info), 3 (debug)
    predict_y=xgb_model.predict(tune_valid_x)
    f1,mcc,roc_auc,table=get_score(tune_valid_y[y_feature].values,predict_y)
    return 'loss':-mcc,'status': STATUS_OK

def xgb_hyper_tune():
    mdep=list(range(2,20))
    space={'max_depth':hp.choice('max_depth',mdep),
        'colsample_bytree':hp.uniform('colsample_bytree',0.1,0.9),
        'learning_rate':hp.quniform('learning_rate',0.01,0.2,0.01),
        'reg_alpha':hp.uniform('reg_alpha',0.1,6.0),
        'reg_lambda':hp.uniform('reg_lambda',0.1,6.0)}

    trials=Trials()
    best_param=fmin(xgb_classifier_tune,space,algo=tpe.suggest,max_evals=100, trials=trials)
    return best_param

Answer 1

因为 hp.choice 将返回索引而不是限制中项目的值。例如，0表示max_depth的值为2。