Implementation of Multi-Class Adaboost algorithm in Mlpack.
by Udit Saxena for mlpack: scalable C++ machine learning library
AdaBoost, short for Adaptive Boosting, uses an ensemble of weak classifiers for classification, after tweaking subsequent weak learners in favor of previously misclassified instances. This project aims at providing a multi-class implementation of the AdaBoost algorithm for Mlpack. Implementing AdaBoost would not only extend the range of the project, but adding weak learners would create a template for other ensemble classification algorithms like Gradient Boosting & LP Boost.