What Does AdaBoost Mean?
AdaBoost is a type of algorithm that uses an ensemble learning approach to weight various inputs. It was designed by Yoav Freund and Robert Schapire in the early 21st century. It has now become somewhat of a go-to method for different kinds of boosting in machine learning paradigms.
Techopedia Explains AdaBoost
Experts talk about AdaBoost as one of the best weighted combinations of classifiers – and one that is sensitive to noise, and conducive to certain machine learning results. Some confusion results from the reality that AdaBoost can be used with multiple instances of the same classifier with different parameters – where professionals might talk about AdaBoost “having only one classifier” and get confused about how weighting occurs.
