Dummy variables

Akin to a chameleon adapting its colors, dummy variables are binary numerical variables created to represent categorical data, allowing the diverse shades of qualitative attributes to be compatible with the mathematical workings of machine learning models and statistical analyses.

Example

Consider a dataset containing information about employees, with a categorical variable representing their employment status (e.g., 'full-time', 'part-time', or 'contract'). To include this information in a machine learning model or statistical analysis that requires numerical input, dummy variables can be created for each category. In this case, two new binary variables might be created: 'Is_full_time' and 'Is_part_time'. A full-time employee would be represented as [1, 0], a part-time employee as [0, 1], and a contract employee as [0, 0]. This transformation enables the model or analysis to effectively incorporate the categorical information.

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