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Categorical data: Difference between revisions
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{{see also|Machine learning terms}} | {{see also|Machine learning terms}} | ||
==Introduction== | ==Introduction== | ||
In [[machine learning]], categorical data represents qualitative or nominal [[feature]]s rather than numerical or [[continuous | In [[machine learning]], categorical data represents qualitative or nominal [[feature]]s rather than numerical or [[continuous feature]]s. It often represents attributes or characteristics of objects or events which cannot be quantified quantitatively. Categorical data plays an essential role in many machine learning tasks such as [[classification]], [[clustering]] and [[regression]]. | ||
Categorical data is sometimes known as [[discrete feature]]s. | Categorical data is sometimes known as [[discrete feature]]s. | ||