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

1 vote323 views1 answer
Python compare two json objects and get difference
Python
20 votes281 views4 answers
Add input to list python
Python
0 vote293 views1 answer
Backend not found Request Method: GET Request URL: http://127.0.0.1:8000/oauth/login/google-oauth2/ Raised by: social_django.views.au
Python
0 vote296 views1 answer
Check if entry is NaT]
Python
2 votes286 views2 answers
How to get key of a particular value in dictionary python using index
Python
0 vote295 views2 answers
Scrapy capture: Error downloading
Python
6 votes306 views2 answers
How to change background of tkinter window
Python
0 vote298 views1 answer
Df filter out rows that appear more than x times
Python
3 votes301 views1 answer
WKUP2 in stm32 microcontroller
Python
1 vote303 views1 answer
Write a python program to find gcd of two numbers
Python