Python 3.x Ridge and Lasso回归-ValueError:输入包含NaN、无穷大或对于数据类型（'；float64'；）太大的值

需要有关错误消息的帮助吗

params = {'alpha': [0.0001, 0.001, 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 20, 50, 100, 500, 1000 ]}
    
    
    ridge = Ridge()
    
    # cross validation
    folds = 5
    model_cv = GridSearchCV(estimator = ridge, 
                            param_grid = params, 
                            scoring= 'neg_mean_absolute_error', 
                            cv = folds, 
                            return_train_score=True,
                            verbose = 1)            
    model_cv.fit(X_train, y_train)

ValueError: Input contains NaN, infinity or a value too large for dtype('float64').   

错误消息

params = {'alpha': [0.0001, 0.001, 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 20, 50, 100, 500, 1000 ]}
    
    
    ridge = Ridge()
    
    # cross validation
    folds = 5
    model_cv = GridSearchCV(estimator = ridge, 
                            param_grid = params, 
                            scoring= 'neg_mean_absolute_error', 
                            cv = folds, 
                            return_train_score=True,
                            verbose = 1)            
    model_cv.fit(X_train, y_train)

ValueError: Input contains NaN, infinity or a value too large for dtype('float64').   

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我试过这一步，它成功了

X = X.fillna(X.interpolate())

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我试过这一步，它成功了

X = X.fillna(X.interpolate())