MATLAB Implementation of ID3 Algorithm with Decision Tree Visualization

Implementation of ID3 algorithm with tree-structured results display. Decision trees classify data for predictive purposes. This method constructs decision trees from training data, and if the tree fails to correctly classify all instances, exceptions are added to the training set. The process iterates until an accurate decision set is formed. Key implementations include entropy calculation, information gain optimization, and recursive tree building functions.