A Sequential Learning Approach for Scaling Up Filter-Based Feature Subset Selection

IEEE Transactions on Neural Networks and Learning Systems
Gregory DitzlerRobi Polikar

Abstract

Increasingly, many machine learning applications are now associated with very large data sets whose sizes were almost unimaginable just a short time ago. As a result, many of the current algorithms cannot handle, or do not scale to, today's extremely large volumes of data. Fortunately, not all features that make up a typical data set carry information that is relevant or useful for prediction, and identifying and removing such irrelevant features can significantly reduce the total data size. The unfortunate dilemma, however, is that some of the current data sets are so large that common feature selection algorithms-whose very goal is to reduce the dimensionality-cannot handle such large data sets, creating a vicious cycle. We describe a sequential learning framework for feature subset selection (SLSS) that can scale with both the number of features and the number of observations. The proposed framework uses multiarm bandit algorithms to sequentially search a subset of variables, and assign a level of importance for each feature. The novel contribution of SLSS is its ability to naturally scale to large data sets, evaluate such data in a very small amount of time, and be performed independently of the optimization of any classifi...Continue Reading

References

Aug 27, 2005·IEEE Transactions on Pattern Analysis and Machine Intelligence·Hanchuan PengChris Ding
Aug 28, 2007·Bioinformatics·Yvan SaeysPedro Larrañaga
Sep 29, 2009·Annals of Statistics·Larry Wasserman, Kathryn Roeder
Jun 1, 2011·Genome Biology·J Gregory CaporasoRob Knight
Feb 22, 2012·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Cosmin LazarAnn Nowé
Mar 23, 2013·IEEE Transactions on Pattern Analysis and Machine Intelligence·Xindong WuXingquan Zhu
Nov 1, 2013·European Journal of Nutrition·Bojana Bogovič MatijašićIrena Rogelj
Mar 21, 2015·IEEE Transactions on Neural Networks and Learning Systems·Gregory DitzlerGail Rosen

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