Feature Selection Algorithms

Feature Selection Algorithms

ID:39771811

大小:326.45 KB

页数:19页

时间:2019-07-11

Feature Selection Algorithms_第1页
Feature Selection Algorithms_第2页
Feature Selection Algorithms_第3页
Feature Selection Algorithms_第4页
Feature Selection Algorithms_第5页
资源描述:

《Feature Selection Algorithms》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库

1、FeatureSelectionAlgorithms:ASurveyandExperimentalEvaluationLuisCarlosMolina,LluísBelanche,ÀngelaNebotUniversitatPolitècnicadeCatalunyaDepartamentdeLlenguatgesiSistemesInformáticsJordiGirona1-3,CampusNordC6,08034,Barcelona,Spain.{lcmolina,belanche,angela}@lsi.upc.esAbstractTheFSAscanbeclassified

2、accordingtothekindofout-puttheyyield:(1)thosealgorithmsgivinga(weighed)lin-Inviewofthesubstantialnumberofexistingfeaturese-earorderoffeaturesand(2)thosealgorithmsgivingasubsetlectionalgorithms,theneedarisestocountoncriteriathatoftheoriginalfeatures.Bothtypescanbeseeninanunifiedenablestoadequate

3、lydecidewhichalgorithmtouseincer-waybynotingthatin(2)theweightingisbinary.tainsituations.Thisworkreviewsseveralfundamentalal-TheworkpresentedinthispaperiscenteredinFSAsgorithmsfoundintheliteratureandassessestheirperfor-tacklingthefeatureselectionproblemoftype(2),studiedmanceinacontrolledscenar

4、io.Ascoringmeasureranksformanyyearsbythestatistical[18]aswellasthemachinethealgorithmsbytakingintoaccounttheamountofrel-learning[38]communities.Researchdevelopedwithintheevance,irrelevanceandredundanceonsampledatasets.machinelearningareaisusuallyfocusedontheproposalofThismeasurecomputesthedegr

5、eeofmatchingbetweenthenewalgorithms,theoreticallearningresultsofexistingal-outputgivenbythealgorithmandtheknownoptimalsolu-gorithmsorempiricalstudies(evaluationsorapplications).tion.Samplesizeeffectsarealsostudied.Inthisresearch,severalfundamentalalgorithmsfoundintheliteraturearestudiedtoasses

6、stheirperformancein1.Introductionacontrolledscenario.Tothisend,ameasuretoevaluateFSAsisproposedthattakesintoaccounttheparticulari-tiesofrelevance,irrelevanceandredundanceonthesam-Thefeatureselectionproblemintermsofsupervisedin-pledataset.Thismeasurecomputesthedegreeofmatchingductivelearningis:

7、givenasetofcandidatefeaturesselectbetweentheoutputgivenbyaFSAandtheknownoptimalasubsetdefinedbyoneofthreeapproaches:a)thesubsetsolution.Samplesizeeffectsarealsostudied.Theresultswithaspecifiedsizethatoptimizesanevaluationmeasure,illustrat

当前文档最多预览五页,下载文档查看全文

此文档下载收益归作者所有

当前文档最多预览五页,下载文档查看全文
温馨提示:
1. 部分包含数学公式或PPT动画的文件,查看预览时可能会显示错乱或异常,文件下载后无此问题,请放心下载。
2. 本文档由用户上传,版权归属用户,天天文库负责整理代发布。如果您对本文档版权有争议请及时联系客服。
3. 下载前请仔细阅读文档内容,确认文档内容符合您的需求后进行下载,若出现内容与标题不符可向本站投诉处理。
4. 下载文档时可能由于网络波动等原因无法下载或下载错误,付费完成后未能成功下载的用户请联系客服处理。