Label binarizer

>>> from sklearn import preprocessing
>>> lb = preprocessing.LabelBinarizer()
>>> lb.fit([1, 2, 6, 4, 2])
LabelBinarizer()
>>> lb.classes_
array([1, 2, 4, 6])
>>> lb.transform([1, 6])
array([[1, 0, 0, 0],
       [0, 0, 0, 1]])

Sklearn labelbinarizer in pipeline

from sklearn.preprocessing import LabelBinarizer

class LabelBinarizerPipelineFriendly(LabelBinarizer):
    def fit(self, X, y=None):
        """this would allow us to fit the model based on the X input."""
        super(LabelBinarizerPipelineFriendly,self).fit(X)
    def transform(self, X, y=None):
        return super(LabelBinarizerPipelineFriendly, self).transform(X)
    def fit_transform(self, X, y=None):
        return super(LabelBinarizerPipelineFriendly, self).fit(X).transform(X)

Source: github.com

Similar codes

0 vote157 views1 answer
Check check writability of the file
Python
0 vote187 views1 answer
Move mouse round in python
Python
0 vote112 views1 answer
List.fold_left
Python
1 vote154 views1 answer
Python how much memory does a variable need
Python
6 votes205 views2 answers
File base name and extension python
Python
0 vote181 views1 answer
Pandas iat 0
Python
212 votes222 views6 answers
Generate random number python
Python
1 vote229 views1 answer
Python try then change something and try again if fails
Python
0 vote168 views2 answers
How to download file in python
Python
14 votes167 views4 answers
Python permutation
Python