sklearn： TypeError： fit() 缺少 1 个必需的位置参数： 'x'

Question

尝试运行此内容时

from sklearn.impute import SimpleImputer
imputer = SimpleImputer(missing_values ="NaN", strategy = "mean")
imputer = SimpleImputer.fit(X[:,1:3])
X[:,1:3] = SimpleImputer.transform(X[:,1:3])

我收到错误

类型错误： fit（） 缺少 1 个必需的位置参数："X"

但是我已经提供了x，对吧？对此的解决方案是什么？

Answer 1

根据这个Scikit-learn模块，正确的语法应该是：

imputer.fit(X[:,1:3])

而不是：

imputer = SimpleImputer.fit(X[:,1:3])

Answer 2

完全工作的代码如下所示：

from sklearn.impute import SimpleImputer
imputer = SimpleImputer(missing_values = np.nan, strategy = "mean")
imputer = imputer.fit(X[:,1:3])
X[:,1:3] = imputer.transform(X[:,1:3])

请注意：

missing_values = np.nan

Answer 3

您的代码：

from sklearn.impute import SimpleImputer
# PAY ATTENTION: to NaN as np.nan
imputer = SimpleImputer(**missing_values ="NaN"**, strategy = "mean")
imputer = SimpleImputer.fit(X[:,1:3])
# PAY ATTENTION: instead of "SimpleImputer.transform" use "imputer.transform"
X[:,1:3] = **SimpleImputer**.transform(X[:,1:3])

正确的代码 ：

from sklearn.impute import SimpleImputer  
imputer = SimpleImputer(missing_values=np.nan, strategy='mean',fill_value=None, verbose=0, copy=True)  
imputer = imputer.fit(X[:, 1:3])  
X[:, 1:3] = imputer.transform(X[:, 1:3])