Explore MATLAB source code curated for "决策树算法" with clean implementations, documentation, and examples.
Implementation of ID3 decision tree algorithm using MATLAB's built-in toolbox functions for tree visualization and corresponding rule generation, featuring entropy-based attribute selection and recursive partitioning.
MATLAB implementation of the CART (Classification and Regression Trees) algorithm for decision trees, featuring robust functionality and optimized performance for classification and regression tasks.
C4.5 Decision Tree Algorithm Source Code. C4.5 is a classic algorithm in the decision tree domain, with academic book citations exceeding 10,000 times. Implementation includes key components like information gain ratio calculation, tree pruning mechanisms, and support for handling both continuous and discrete attributes.
A comprehensive MATLAB implementation of decision tree algorithm with detailed explanations and code descriptions