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

Question

尝试运行此

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])

我遇到错误

  

TypeError：fit（）缺少1个必需的位置参数：“ X”

但是我已经提供了x，对不对？ 解决方案是什么？

Answer 1

根据this Scikit-learn module，正确的语法应为：

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

代替：

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

Answer 2

完全工作的代码如下：

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：

def add_to_db(d):
    report  = Report(**d)
    db.session.add(report)
    db.session.commit()

正确的代码：

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])