Data Science PRFeatures having a discrete set of possible values. For example, consider a categorical feature named house style, which has a discrete set of three possible values: Tudor, ranch, colonial. By representing house style as categorical data, the model can learn the separate impacts of Tudor, ranch, and colonial on house price.
Sometimes, values in the discrete set are mutually exclusive, and only one value can be applied to a given example. For example, a car maker categorical feature would probably permit only a single value (Toyota) per example. Other times, more than one value may be applicable. A single car could be painted more than one different color, so a car color categorical feature would likely permit a single example to have multiple values (for example, red and white).
Categorical features are sometimes called discrete features.
Contrast with numerical data.
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