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MATLAB implementation of a decision tree based on ID3 capable of binary classification and handling of continuous features.

Open classifier.m, insert your training and test data, and run it. Data entry instructions are described in the script file. Datasets with both continuous and categorical features are supported.

  • classifier.m contains training and test data, as well as fit and predict function calls.

  • tree_fit.m builds a decision tree classifier from the provided training set. It returns a tree in the form of a cell array.

  • tree_predict.m predicts the classes of the test set. It returns a vector that contains the class predictions.

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MATLAB implementation of a decision tree based on ID3 capable of binary classification and handling of continuous features

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