Discretization of continuous features

This can be useful when creating probability mass functions – formally, in density estimation.

It is a form of discretization in general and also of binning, as in making a histogram.

The goal is to reduce the amount to a level considered negligible for the modeling purposes at hand.

[1] Mechanisms for discretizing continuous data include Fayyad & Irani's MDL method,[2] which uses mutual information to recursively define the best bins, CAIM, CACC, Ameva, and many others[3] Many machine learning algorithms are known to produce better models by discretizing continuous attributes.

[4] This is a partial list of software that implement MDL algorithm.