Binary encoding

Binary encoding is a technique used for encoding categorical features by converting each category into binary code. Each unique category is represented by a unique binary pattern, where each digit (0 or 1) in the pattern corresponds to the presence or absence of that category. Binary encoding is particularly useful for handling high-cardinality categorical features while reducing dimensionality.

When to use binary encoding

Binary encoding can be considered in the following scenarios:

• Dimensionality reduction: You want to reduce the dimensionality of the dataset while still capturing information contained within the categorical feature. Binary encoding is particularly useful in this scenario.
• Efficiency: You need an efficient encoding method that results in a compact representation of categorical data and can be easily processed by ML algorithms.

Let’s look at a use case.

Use case – customer subscription prediction

A subscription...