Subspace Learning Machine (SLM): A New Approach to Classification and Regression

Author(s):

Vinod K Mishra and C-C Jay Kuo

Abstract:

Classification and regression are some of the most important tasks handled by supervised machine learning. Many approaches like feedforward multilayer perceptron, decision tree, support vector machines, and extreme learning machine methods have been proposed in the past for these tasks. Recently, a new approach called subspace learning machine/regressor (SLM/SLR) has been applied to data with low to moderate dimensions and it has shown substantial advantages over other similar methods. This technical report describes SLM/SLR and traces the reasons behind its superior performance.