CAIM Discretization Algorithm

CAIM (class-attribute interdependence maximization) is designed to discretize continuous data.

The task of extracting knowledge from databases is quite often performed by machine learning algorithms. The majority of
these algorithms can be applied only to data described by discrete numerical or nominal attributes (features). In the case of continuous attributes, there is a need for a discretization algorithm that transforms continuous attributes into discrete ones.
This code is based on paper: "CAIM Discretization Algorithm", details can look for this paper [1].
One can start with "ControlCenter.m", here you will find a simple example , with explanations.
If there is any problem , please let me know. I will answer you as soon as possible.

[1] Kurgan, L. and Cios, K.J., 2004. CAIM Discretization Algorithm. IEEE Transactions on Knowledge and Data Engineering, 16(2):145-153