ambarmodi / Decision-Tree

Implementation of Decision tree as a predictive(supervised) learning model. The implementation uses ID3 algorithm and also the Information Gain Heuristic and Variance Impurity Heuristic.

Decision-Tree

Implement the decision tree learning algorithm using Information gain heuristic and Variance impurity heuristic

Instructions to execute:

1. make (This will compile the program)
2. java ProgramDT training-set validation-set test-set to-print (This will generate both the inorder and out-of-order output_file)
3. make clean (Optional : This will clean compiled .class files)

Output of the program:

1. if is 'yes' then Program will print Trees using both Heuristic and respective accuracies
2. if is 'no' then Program will print accuracies of DT for both Heuristics