Python 网格搜索输入包含NaN、无穷大或对数据类型太大的值(';float64';)

Python 网格搜索输入包含NaN、无穷大或对数据类型太大的值(';float64';),python,machine-learning,scikit-learn,nan,grid-search,Python,Machine Learning,Scikit Learn,Nan,Grid Search,这是使用scikit库运行网格搜索代码时出现的错误 Input contains NaN, infinity or a value too large for dtype('float64') 我尝试使用dropna()并确保没有任何nan值 df= pd.read_csv('train.csv') df.dropna(inplace=True) X_train, X_test, y_train, y_test= train_test_split(df.drop(columns=['SaleP

这是使用scikit库运行网格搜索代码时出现的错误

Input contains NaN, infinity or a value too large for dtype('float64')
我尝试使用dropna()并确保没有任何nan值

df= pd.read_csv('train.csv')
df.dropna(inplace=True)
X_train, X_test, y_train, y_test= train_test_split(df.drop(columns=['SalePrice']), df['SalePrice'], random_state=1)
mlp = MLPRegressor(max_iter=1000, hidden_layer_sizes=(667, 45, 45), random_state=1 )
parameter_space = {
    'activation': ['tanh', 'relu', 'identity', 'logistic'],
    'solver': ['sgd', 'adam', 'lbfgs'],
    'alpha': [0.0001, 0.05],
    'learning_rate': ['constant','adaptive'],
}

clf = GridSearchCV(mlp, parameter_space, n_jobs=-1, cv=3, scoring='neg_mean_squared_log_error')
clf.fit(X_train.values, y_train.values)


但仍然返回相同的错误。为什么?

检查df size[df.shape],它可能是空的,或者数据帧具有非数字值df size=
(840,312)
检查df size[df.shape],它可能是空的,或者数据帧具有非数字值df size=
(840,312)
df.isnull().any().any()
# False