Mastering Machine Learning Algorithms

AdaBoost.SAMME

This variant, called Stagewise Additive Modeling using a Multi-class Exponential loss (SAMME), was proposed by Zhu, Rosset, Zou, and Hastie in Multi-class AdaBoost, Zhu J., Rosset S., Zou H., Hastie T., 01/2006. The goal is to adapt AdaBoost.M1 in order to work properly in multi-class scenarios. As this is a discrete version, its structure is almost the same, with a difference in the estimator weight computation. Let's consider a label dataset, Y:

Now, there are p different classes and it's necessary to consider that a random guess estimator cannot reach an accuracy equal to 0.5; therefore, the new estimator weights are computed ...