One Hot Vector
One hot vector is used to encode words into a vector of 0 and 1. The dimension for each word vector is the vocabulary size. For each word, one column is set to 1 and others are set to 0.
It is a very good metric if the feature is categorical and has medium cardinality.
Issues:
- Expensive computation as it becomes very large, very quickly
- High memory consumption due to it high sparsity.
Tips to use:
- Make the cardinal smaller by using other classes
- Make sure that unseen data on the test time is handled