Problem Description:

In order to transform numerical data to categorical data, descretization algorithms are used. These algorithms are also called binning algorithms. There are two types of binning algorithms: equal width and equal frequncy (depth).

In equal-width binning algorithms, the width (the difference between the possible min and max values) are roughly the same for each bin.

In equal-frequency binning algorithms, each bin would contain roughly the same number of data items in the end.

Here is a set of data that will also be used in the assignment 1: A1-data.csv. The attribute "AGE" is a continuous attribute. In order to build a decision tree using the given data set, the values in the "AGE" attribute need to be split into two categories.

Your tasks:

• Design and implement your own algorithm that split "AGE" attribute values into two categories using equal-width method.
• Design and implement your own algorithm that split "AGE" attribute values into two categories using equal-frequency method.