Binary Vector

A binary vector is a sequence of 1s and 0s (bits) that represent data in a binary format.

It is used when there is a need to represent data in a compact and efficient manner, such as in binary classification or feature representation. Binary vectors are commonly applied in scenarios such as image processing, data compression, and machine learning models that use binary features. The technique works by encoding data as a series of bits, where each bit represents a binary state (0 or 1).

Using One-Hot Encoding, most data can ultimately be represented as a binary vector, which blurs the distinction between binary vectors and vectors of categorical variables. In this catalogue, the term “binary vector” is used to refer to cases where data cannot sensibly be described as a vector of variables (e.g., an image bitmap) or where a vector of variables consists exclusively of independent booleans.

Binary vectors are important because they provide a simple and efficient way to represent data, enabling models to process and analyze binary information effectively.