Summary: Novel Methods for the Feature Subset Ensembles Approach
Mohamed A. Aly
Electrical Engineering, Caltech, Pasadena, CA 91125
mohamedadaly@gmail.com
Amir F. Atiya
Dept Computer Engineering, Cairo University, Giza, Egypt
amiratiya@link.net
Abstract
Ensemble learning technique attracted much attention in
the past few years. Instead of using a single prediction
model, this approach utilizes a number of diverse accu-
rate prediction models to do the job. Many methods have
been proposed to build such accurate diverse ensembles, of
which bagging and boosting were the most popular. An-
other method, called Feature Subset Ensembles FSE, is
thoroughly investigated in this work. This technique builds
ensembles by assigning each individual prediction model
in the ensemble a distinct feature subset from the pool of
available features. In this paper several novel variations
to the basic FSE are proposed. Extensive comparisons are

Source: Abu-Mostafa, Yaser S. - Department of Mechanical Engineering & Computer Science Department, California Institute of Technology

Collections: Computer Technologies and Information Sciences