Python sci kit发现TransformerMixin具有奇怪的适合转换行为

继承自

TransformerMixin

的

fit\u transform

方法不会将

y

变量传递给

transform

方法。 这里有一个最小的例子

class UslessPrint(BaseEstimator, TransformerMixin):
    def __init__(self):
        pass
    def fit(self, X, y=None):
        print(y)
        return self
    def transform(self, X, y=None):
        print(y)
        return X

usless = mc.UslessPrint()
usless.fit_transform([[1, 2], [2, 1]], [0, 1])

输出为：

[0, 1]
None

而不是预期的

[0, 1]
[0, 1]

---

这种行为是正常的，还是一个bug。

这是

TransformerMixin

的预期行为，而不是bug

sklearn.Base.TransformerMixin

的

fit\u transform

在其

transform

中不使用

y

发件人：

如您所见，

TransformerMixin

仅将

X

传递给

transform

，将

y

保留为代码中的

None

class TransformerMixin(object):
    """Mixin class for all transformers in scikit-learn."""

    def fit_transform(self, X, y=None, **fit_params):
        """Fit to data, then transform it.
        Fits transformer to X and y with optional parameters fit_params
        and returns a transformed version of X.
        Parameters
        ----------
        X : numpy array of shape [n_samples, n_features]
            Training set.
        y : numpy array of shape [n_samples]
            Target values.
        Returns
        -------
        X_new : numpy array of shape [n_samples, n_features_new]
            Transformed array.
        """
        # non-optimized default implementation; override when a better
        # method is possible for a given clustering algorithm
        if y is None:
            # fit method of arity 1 (unsupervised transformation)
            return self.fit(X, **fit_params).transform(X)
        else:
            # fit method of arity 2 (supervised transformation)
            return self.fit(X, y, **fit_params).transform(X)