* `Xt` [array-like, shape=(n_samples, n_categories)]:
The one-hot encoded categories.
return self._lb.transform(X)
def inverse_transform(self, Xt):
Inverse transform one-hot encoded categories back to their original
representation.
After Change
* `Xt` [array-like, shape=(n_samples, n_categories)]:
The one-hot encoded categories.
return self._lb.transform([self.mapping[v] for v in X])
def inverse_transform(self, Xt):
Inverse transform one-hot encoded categories back to their original
representation.