Complete Tutorial: Random Forests Machine Learning with MATLAB

This tutorial provides a complete introduction to Random Forests in MATLAB, combining the essential theory with practical implementation. It explains how random forests work for both classification and regression, how bagging and random feature selection improve performance, and how to build models in MATLAB using tools such as TreeBagger, fitcensemble, fitrensemble, predict, out-of-bag error analysis, predictor importance, and the Classification Learner and Regression Learner apps.

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