Discretization MDLP

Python implementation of Fayyad and Irani's MDLP criterion discretiation algorithm

Reference:

Irani, Keki B. "Multi-interval discretization of continuous-valued attributes for classification learning." (1993).

Instructions:

1. Download Entropy.py and MDLPC.py
2. In a terminal, cd into the directory where the .py files were saved
3. run the following command: python MDLPC.py --options=...

script options:

• in_path (required): Path to dataset in .csv format (must include header)
• out_path (required): Path where the discretized dataset will be saved
• features (optional): comma-separated list of attribute names to be discretized, e.g., features=attr1,attr2,attr3
• class_label (required): label of class column in .csv dataset
• return_bins (optional): Doesn't take on values. If specified (--return_bins), a text file will be saved in the same directory as out_path. This file will include the description of the bins computed by the algorighm.

Dependencies:

1. Pandas
2. Numpy