Hunts algorithm is decision tree growth algorithm which is a widely used classification technique in Data mining.
Features
- The module will construct a decision tree on any data set based on the training records.
- Handles both discrete and continuous attributes and used multi-way split for continuous and binary split for discrete
- Uses Gini index or Entropy or classication error combined with Gain ratio to find the split attribute
- Builds the decision tree till the node contains only a specific class attribute or reaches a minimum threshold on which it becomes a leaf node
- Measures the accuracy on the training as well as the testing records
Methodology
- Inheritance and recursion played a key role in the implementation of the algorithm
Programming Language : Java in Model View Controller design pattern