Looking inside ensembles of negatively correlated Self-Organizing Maps. [Elektronische Ressource] / Alexandra Scherbart. Technische Fakultät - AG Neuroinformatik

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desBielefeldvUniverersittyAlexandraFtacultsyoofGradesTuaryecthnologylBioDdataeMiningt&zurAppliedademiscNveuroinformaticsherbartGroup2011Losio?kinBielefegdInsideorgelegteEnsemblesiofsnegativelyrcoarrelatediSelf-OrganizingnMapsErlangungDerakThenecDr.-Ing.hnisconhenScFJanakult?t9,derUniverSupNattkervisor:W.JunProf.empDr.TimypingList.of.FiguresHandlingvii.List.of.T.ables.ix.Glossavry.xi.1.Intro.duction.1.1.1erformancePComparisoneak.In.teeighn.si15t.yEvPrediction......25.......P...2.3.5.4.............b.the.......V.......on..1.1.2.Bias2.3.4and.V.ariance.and.the.T.rade-O..2.3.5.1...........2.3.5.3.NG.eptides.....of.Discussion.......33......3.1.3InWhey.applyeV.ector-Quan.tizLeastat.i.on.Based-SuppSelf-OrganizingMacMaps?..........20.uat4.1.4.Wh.y.Ens.e.m.ble.Learning?in.............Results.................eptide...........2.3.5.2.In......6.1.5PredictionPSOMoten.tialofof.SOM.Ensem.ble.Learning29.P.eature.31.................Conclusions...............2.47P1.6yOutlineA.eature...2.4.1.eature.ance.........2.4.1.1.uares.........38...2.3.2Contents.ort.ector.hine.......................2.3.3.al.i..9.1.7.Publications........................23.Issues.Data.........................2.3.5..............10.2.P.eak.Intensit.y.Prediction.in.a.Single26LeaPrnerPrototS.etup.11.2.1.MS.data..........26.Predicting.eaks'.tensities...............27.Comparison.P.of.to...28.Subsampling.P...................2.3.5.5.Prediction.erformance13F2.2SetsBenc.hmark2.3.6Datasets................................2.3.7.....

Sujets

• Informatik

Informations

• Publié par: universitat_bielefeld
• Publié le: 01 janvier 2011
• Nombre de lectures: 16
• Poids de l'ouvrage: 8 Mo

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