Glossary term
Glossary term
Foundations
Features having a specific set of possible values. For example, consider a categorical feature named traffic-light-state, which can only have one of the following three possible values:
red
yellow
green
By representing traffic-light-state as a categorical feature, a model can learn the differing impacts of red, green, and yellow on driver behavior.
Categorical features are sometimes called discrete features.
Contrast with numerical data.
See Working with categorical data in Machine Learning Crash Course for more information.
Created for this library
A retail data team treats payment_method and store_region as categorical data and one-hot encodes them before training a logistic regression on cart-abandonment risk.
An HR analytics team treats job_family as categorical data and embeds it for use in an attrition model alongside numeric features.
A telco churn team treats plan_tier as categorical data and uses target encoding to convert it into a numeric feature for its boosted-tree model.
Definition source: Google for Developers Machine Learning Glossary | Creative Commons Attribution 4.0 License