OneHotEncoding-Technique-Data-Encoding-Method

Process of converting a categorical features values into meaningful numerical values. OneHotEncoding is a method to convert categorical data into a binary (0 or 1) format so that it can be used in machine learning models. Each unique category becomes a new column, and a row has 1 in the column of its category and 0s elsewhere.

eg. Consider a feature in a dataset have three values as red, Green and Blue.

Then we can write them as binary vector where each bit correspond to a unique category.

Red Green Blue

1 0 0 <---Red

0 1 0 <---Green

0 0 1 <---Blue