README

Decision Tree Program

File Structure:
decisionTree.py
README.txt
Report.docx
Output.txt

decisionTree.py - It contains the source code of creating a decision tree using ID3 algorithm for the datasets given. 
README.txt - It contains the description of the zip folder.
Report.docx - Assumptions and best results of the algorithm implementation.
Output.txt - It contains the output for one run of the code on sample data set 1 which was provided. 

Development Environment:
Decision Tree Learning program was developed in python and tested in both Windows and Linux Operating System.

Usage:
The program is compatible with Python 3.5 and 3.6.

Prerequisite:
The training dataset, test dataset and validation dataset should be in .xlsx format.
The pruning factor should be a decimal number in range from 0.1 to 0.9

Steps to COMPILE and RUN

python decisionTree.py <Path of training data> <Path of Test Data> <Path of Validation Data> <Pruning Factor>