Effect Encoding

Data Science, AI and ML
#1

This encoding technique is also known as Deviation Encoding or Sum Encoding. Effect encoding is almost similar to dummy encoding, with a little difference. In dummy coding, we use 0 and 1 to represent the data but in effect encoding, we use three values i.e. 1,0, and -1.

The row containing only 0s in dummy encoding is encoded as -1 in effect encoding. In the dummy encoding example, the city Bangalore at index 4 was encoded as 0000. Whereas in effect encoding it is represented by -1-1-1-1.