Conference
Regularized Least Squares: A useful (Forgotten) tool for supervised and semi-supervised learning
Abstract
This paper discusses the undervalued importance of Regularized Least Squares, and its continued usefulness in solving supervised and semisupervised learning problems. The common two moon classification problem was used to study and compare the effectiveness of three methods: the Support Vector Machine (Radial Basis Functions and 6 th Order Polynomials), Laplacian Regularized Least Squares, and K-Means with Regularized Least Squares (KM-RLS). …
Authors
Gadsden SA; Mohammed D; Al-Shabi M
Volume
3
Pagination
pp. 40-44
Publication Date
December 1, 2009
Conference proceedings
Wmsci 2009 the 13th World Multi Conference on Systemics Cybernetics and Informatics Jointly with the 15th International Conference on Information Systems Analysis and Synthesis Isas 2009 Proc