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 vote173 views1 answer
Python index strings
Python
0 vote211 views1 answer
How to find left top width and height on an image using python
Python
0 vote247 views1 answer
Django charfield force lowercase
Python
49 votes247 views10 answers
Reddit
Python
0 vote210 views1 answer
Value keys in dictionary are immutable true/false
Python
0 vote229 views1 answer
One small letter three big bodyguard
Python
1 vote233 views1 answer
How to run python file from cmd in dockerfile
Python
0 vote248 views1 answer
Selenium press tab python
Python
1 vote198 views1 answer
Plt.plot width line
Python
0 vote205 views1 answer
Instal django impoer expor
Python