categorical data

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.

Practitioners refer to categorical data when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.