Boosting Algorithm: Adaboost Implementation and Theory

Adaboost Algorithm with MATLAB Implementation - An iterative machine learning method that trains multiple weak classifiers on the same dataset and combines them into a powerful ensemble classifier through weighted voting mechanisms.

Adaboost_M1 - Ensemble Method for Combining Multiple Classifiers

A MATLAB implementation of Adaboost_M1 algorithm, primarily designed for bundling different classifiers. This implementation demonstrates a practical approach to boosting methodology.

LogitBoost: An Enhanced Boosting Algorithm for Classification Tasks

LogitBoost represents an improved boosting algorithm that optimizes logistic loss functions for enhanced classification performance and probability output capabilities.