类型错误：__init__() 有一个意外的关键字参数“reg_alpha”答案

【问题标题】：Type Error: __init__() got an unexpected keyword argument 'reg_alpha'类型错误：__init__() 有一个意外的关键字参数“reg_alpha”
【发布时间】：2020-10-28 09:09:00
【问题描述】：

使用随机搜索 CV 查找 CatboostClassfier 模型的参数时。我收到类型错误：这是我的代码sn-p。我为这个问题寻找了 catboost 库，但找不到它。是什么导致了这种类型的 Type_error？

para={
 "n_estimators"     : [1000,5000,10000],
 "learning_rate"    : [0.05, 0.10, 0.15, 0.20, 0.25, 0.30 ] ,
 "max_depth"        : [ 3, 4, 5, 6, 8, 10, 12, 15],
 "reg_alpha"        : [0.4,0.7,1,3],
 "reg_lambda"       : [0.2,0.4,0.7,1,3],  
 "colsample_bytree" : [ 0.3, 0.4, 0.5 , 0.7 ],
 "subsample"        : [ 0.3, 0.5, 0.7, 1] 
    
}

import catboost as cb
cbg = cb.CatBoostClassifier()
random_search=RandomizedSearchCV(cbg,
                                 param_distributions=para,
                                 n_iter=5,
                                 scoring='roc_auc',
                                 n_jobs=-1,
                                 cv=5,
                                 verbose=3)
random_search.fit(X,y)




TypeError                                 Traceback (most recent call last)
<ipython-input-18-68719ca71dd9> in <module>
----> 1 random_search.fit(X,y)

~\Anaconda3\envs\py3.6-TF2.3\lib\site-packages\sklearn\utils\validation.py in inner_f(*args, **kwargs)
     70                           FutureWarning)
     71         kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---> 72         return f(**kwargs)
     73     return inner_f
     74 

~\Anaconda3\envs\py3.6-TF2.3\lib\site-packages\sklearn\model_selection\_search.py in fit(self, X, y, groups, **fit_params)
    760             # of the params are estimators as well.
    761             self.best_estimator_ = clone(clone(base_estimator).set_params(
--> 762                 **self.best_params_))
    763             refit_start_time = time.time()
    764             if y is not None:

~\Anaconda3\envs\py3.6-TF2.3\lib\site-packages\sklearn\utils\validation.py in inner_f(*args, **kwargs)
     70                           FutureWarning)
     71         kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---> 72         return f(**kwargs)
     73     return inner_f
     74 

~\Anaconda3\envs\py3.6-TF2.3\lib\site-packages\sklearn\base.py in clone(estimator, safe)
     86     for name, param in new_object_params.items():
     87         new_object_params[name] = clone(param, safe=False)
---> 88     new_object = klass(**new_object_params)
     89     params_set = new_object.get_params(deep=False)
     90 

TypeError: __init__() got an unexpected keyword argument 'reg_alpha'

【问题讨论】：

标签： python machine-learning jupyter-notebook xgboost

【解决方案1】：

问题是reg_alpha 不是initializing CatBoostClassifier 的参数。你会发现here 没有列出reg_alpha。对于colsample_bytree，您会发现同样的情况。从参数字典中删除这些将解决错误。

【讨论】：