sklearn passthrough特征选择器

Question

我正在使用sklearn管道，并希望有一个功能选择步骤，可以设置为无功能选择。有没有什么也不做的sklearn.feature_selection.SelectorMixin对象？

编辑:或者至少有一个模板可以开发一个模板，比如可以有一个估计器？

Answer 1

一天结束后，我选择了这样的东西，它似乎符合我现在的目的。但不确定它是否会被验证为正确的sklearn.feature_selection选择器：

import numpy as np
import pandas as pd
from sklearn.utils.validation import check_is_fitted


class PassThroughSelector():
    """
    Simply selects all columns of the dataframe, allowing
    to have the equivalent of no selector without changing
    too much of the structure.

    Args:
    """

    def __init__(self):
        pass
    
    def fit(self, x, y=None):  # pylint:disable=unused-argument, arguments-differ
        """
        Stores a list of selected columns.
        Args:
            x: training data
            y: training y (no effect)
        Returns:
            self
        """
        self.check_x(x)
        mask = np.where(np.ones(len(x.columns)), True, False)
        self.support_ = mask
        self.selected_features_ = x.columns[self.support_].tolist()
        return self

    def get_support(self, indices = False) -> np.ndarray:
        """Provides a boolean mask of the selected features."""
        check_is_fitted(self)
        if indices == True:
            return np.array([i for i in range(len(self.support_)) if self.support_[i]==True])
        else:
            return self.support_

    def transform(self, x: pd.DataFrame):
        """Selects the features selected in `fit` from a provided dataframe."""
        check_is_fitted(self)
        self.check_x(x)
        return x.loc[:, self.support_]

    def get_params(self, deep = True):
        return {}