A survey of feature selection methods : algorithms and software

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dc.contributor.advisorDimitrov, Nedialko B.en
dc.contributor.committeeMemberMaloney, Andyen
dc.creatorArguello, Bryanen
dc.creator.orcid0000-0001-6813-090Xen
dc.date.accessioned2015-11-12T15:08:49Zen
dc.date.accessioned2018-01-22T22:29:03Z
dc.date.available2015-11-12T15:08:49Zen
dc.date.available2018-01-22T22:29:03Z
dc.date.issued2015-05en
dc.date.submittedMay 2015en
dc.date.updated2015-11-12T15:08:49Zen
dc.descriptiontexten
dc.description.abstractThe feature selection problem is a major component in disease surveillance since data sources are so costly. This report describes several existing methods for performing feature selection along with software that implements these methods. To help make experimenting with different algorithms easy, we have created a feature selection wrapper package in Python. This wrapper allows the user to easily try different algorithms on the same data set and visualize the results. Experiments are performed to validate that the methods perform as expected.en
dc.description.departmentOperations Research and Industrial Engineeringen
dc.format.mimetypeapplication/pdfen
dc.identifierdoi:10.15781/T2S91Pen
dc.identifier.urihttp://hdl.handle.net/2152/32404en
dc.subjectFeature selectionen
dc.subjectSoftwareen
dc.titleA survey of feature selection methods : algorithms and softwareen
dc.typeThesisen

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University of Texas at Austin