請幫我在這段代碼中找到一個 ValueError

Question

# https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.RandomizedSearchCV.html #在這個簡歷中找到最大的alphas來最小化錯誤

    from sklearn.model_selection import RandomizedSearchCV

    #use multinomialnb as a model
    model = MultinomialNB(class_prior = [0.5, 0.5])
    parameters = {'alphas' :[0.00001,0.0005, 0.0001,0.005,0.001,0.05,0.01,0.1,0.5,1,5,10,50,100]}
    
    #use randomizedsearch as a cv 
    clf = RandomizedSearchCV(model, parameters, cv= 5, 
    scoring='roc_auc',verbose=1,return_train_score=True)
    #to fit the model
    clf.fit(X_tr, y_train)#in this line to genrate the error

    #to genrate a dataframe & sort the value
    results = pd.DataFrame.from_dict(clf.cv_results_)
    results = results.sort_values(['param_alphas'])

    #to find a auc result to genrate a auc curve
    train_auc= results['mean_train_score']
    train_auc_std= results['std_train_score']
    cv_auc = results['mean_test_score'] 
    cv_auc_std= results['std_test_score']
    alphas =  results['param_alphas']```


ValueError                                Traceback (most recent call last)
<ipython-input-65-23b8907f0343> in <module>
      7 
      8 clf = RandomizedSearchCV(model, parameters, cv= 5, scoring='roc_auc',verbose=1,return_train_score=True)
----> 9 clf.fit(X_tr, y_train)
     10 
     11 results = pd.DataFrame.from_dict(clf.cv_results_)

ValueError: Invalid parameter alphas for estimator MultinomialNB(alpha=1.0, class_prior=[0.5, 0.5], fit_prior=True). Check the list of available parameters with `estimator.get_params().keys()`.

Answer 1

字典parameters的鍵應該是“alpha”而不是“alphas”。

所以只需將該行更改為：

parameters = {'alpha' :[0.00001,0.0005, 0.0001,0.005,0.001,0.05,0.01,0.1,0.5,1,5,10,50,100]}