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Implementation of Decision Tree using two heuristics for Assignment 01 of the course CS6375: Machine Learning.

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ML-A01: Decision Trees

Implementation of Decision Tree using the two heuristics for Assignment 01 of the course CS6375: Machine Learning.

Problem:

Assignment 01

Solution:

DecisionTrees.java, Report

How to Run:

  1. Compile:
$javac DecisionTrees.java
  1. Execute:
$java DecisionTrees L K training_set.csv validation_set.csv test_set.csv V

L: positive integer (used in post pruning algorithm)

K: positive integer (used in post pruning algorithm)

V: 'yes' or 'no' to print the tree on the command line

NOTE:

  • 10 {L, K} pair-values that are chosen: {30 , 50}, {70 , 100}, {90 , 150}, {100, 200}, {150, 250}, {200, 300}, {300, 400}, {400, 500}, {500, 550}, {600, 600}. for both DataSet-1 and DataSet-2

  • Refer a01-script.sh for more execution guidelines. The results are stored in log/ and log-verbose/ directories.

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