Morethanadecadeago,combiningmultipleclassi?erswasproposedasap- siblesolutiontotheproblemsposedbythetraditionalpatternclassi?cation approachwhichinvolvedselectingthebestclassi?erfromasetofcandidates basedontheirexperimentalevaluation. Asnoclassi?erisknowntobethebest forallcasesandtheselectionofthebestclassi?erforagivenpracticaltaskis verydi?cult,diverseresearchcommunities,includingMachineLearning,N- ralNetworks,PatternRecognition,andStatistics,addressedtheengineering problemofhowtoexploitthestrengthswhileavoidingtheweaknessesofd- ferentdesigns. Thisambitiousresearchtrendwasalsomotivatedbyempirical observationsaboutthecomplementarityofdi?erentclassi?erdesigns,natural requirementsofinformationfusionapplications,andintrinsicdi?cultiesasso- atedwiththeoptimalchoiceofsomeclassi?erdesignparameters,suchasthe architectureandtheinitialweightsforaneuralnetwork. Afteryearsofresearch, thecombinationofmultipleclassi?ershasbecomeawellestablishedandexciting researcharea,whichprovidese?ectivesolutionstodi?cultpatternrecognition problems. Aconsiderablebodyofempiricalevidencesupportsthemeritof- signingcombinedsystemswhoseaccuracyishigherthanthatofeachindividual classi?er,andvariousmethodsforthegenerationandthecombinationofm- tipleclassi?ershavebecomeavailable. However,despitetheprovedutilityof multipleclassi?ersystems,nogeneralanswertotheoriginalquestionaboutthe possibilityofexploitingthestrengthswhileavoidingtheweaknessesofdi?erent classi?erdesignshasyetemerged. Otherfundamentalissuesarealsoamatterof on-goingresearchindi?erentresearchcommunities. Theresultsachievedd- ingthepastyearsarealsospreadoverdi?erentresearchcommunities,andthis makesitdi?culttoexchangesuchresultsandpromotetheircross-fertilization. Theacknowledgmentofthefundamentalrolethatthecreationofacommon internationalforumforresearchersofthediversecommunitiescouldplayfor theadvancementofthisresearch?eldmotivatedthepresentseriesofwo- shopsonmultipleclassi?ersystems. Followingitspredecessors,MultipleCl- si?erSystems2000(SpringerISBN3-540-67704-6)and2001(SpringerISBN 3-540-42284-6),thisvolumecontainstheproceedingsoftheThirdInternational WorkshoponMultipleClassi?erSystems(MCS2002),heldattheGrandHotel ChiaLaguna,Cagliari,Italy,onJune24-26,2002. The29papersselectedby thescienti?ccommitteehavebeenorganizedinsessionsdealingwithbagging andboosting,ensemblelearningandneuralnetworks,combinationstrategies, designmethodologies,analysisandperformanceevaluation,andapplications. Theworkshopprogramandthisvolumeareenrichedwiththreeinvitedtalks givenbyJoydeepGhosh(UniversityofTexas,USA),TrevorHastie(Stanford University,USA),andSarunasRaudys(VilniusGediminasTechnicalUniversity, Lithuania). Papersweresubmittedfromresearchersofthefourdiversecom- nities,socon?rmingthatthisseriesofworkshopscanbecomeacommonforum VI Foreword forexchangingviewsandreportinglatestresearchresults. Asfortheprevious editions,thesigni?cantnumberofpapersdealingwithrealpatternrecognition applicationsareproofofthepracticalutilityofmultipleclassi?ersystems. This workshopwassupportedbytheUniversityofCagliari,Italy,theUniversityof Surrey,Guildford,UnitedKingdom,andtheDepartmentofElectricalandEl- tronicEngineeringoftheUniversityofCagliari. Allthesesupportsaregratefully acknowledged. WealsothanktheInternationalAssociationforPatternRecog- tionanditsTechnicalCommitteeTC1onStatisticalPatternRecognitionTe- niquesforsponsoringMCS2002. Wewishtoexpressourappreciationtoallthose whohelpedtoorganizeMCS2002. Firstofall,wewouldliketothankallthe membersoftheScienti?cCommitteewhoseprofess
"Sinopsis" puede pertenecer a otra edición de este libro.
Morethanadecadeago,combiningmultipleclassi?erswasproposedasap- siblesolutiontotheproblemsposedbythetraditionalpatternclassi?cation approachwhichinvolvedselectingthebestclassi?erfromasetofcandidates basedontheirexperimentalevaluation. Asnoclassi?erisknowntobethebest forallcasesandtheselectionofthebestclassi?erforagivenpracticaltaskis verydi?cult,diverseresearchcommunities,includingMachineLearning,N- ralNetworks,PatternRecognition,andStatistics,addressedtheengineering problemofhowtoexploitthestrengthswhileavoidingtheweaknessesofd- ferentdesigns. Thisambitiousresearchtrendwasalsomotivatedbyempirical observationsaboutthecomplementarityofdi?erentclassi?erdesigns,natural requirementsofinformationfusionapplications,andintrinsicdi?cultiesasso- atedwiththeoptimalchoiceofsomeclassi?erdesignparameters,suchasthe architectureandtheinitialweightsforaneuralnetwork. Afteryearsofresearch, thecombinationofmultipleclassi?ershasbecomeawellestablishedandexciting researcharea,whichprovidese?ectivesolutionstodi?cultpatternrecognition problems. Aconsiderablebodyofempiricalevidencesupportsthemeritof- signingcombinedsystemswhoseaccuracyishigherthanthatofeachindividual classi?er,andvariousmethodsforthegenerationandthecombinationofm- tipleclassi?ershavebecomeavailable. However,despitetheprovedutilityof multipleclassi?ersystems,nogeneralanswertotheoriginalquestionaboutthe possibilityofexploitingthestrengthswhileavoidingtheweaknessesofdi?erent classi?erdesignshasyetemerged. Otherfundamentalissuesarealsoamatterof on-goingresearchindi?erentresearchcommunities. Theresultsachievedd- ingthepastyearsarealsospreadoverdi?erentresearchcommunities,andthis makesitdi?culttoexchangesuchresultsandpromotetheircross-fertilization. Theacknowledgmentofthefundamentalrolethatthecreationofacommon internationalforumforresearchersofthediversecommunitiescouldplayfor theadvancementofthisresearch?eldmotivatedthepresentseriesofwo- shopsonmultipleclassi?ersystems. Followingitspredecessors,MultipleCl- si?erSystems2000(SpringerISBN3-540-67704-6)and2001(SpringerISBN 3-540-42284-6),thisvolumecontainstheproceedingsoftheThirdInternational WorkshoponMultipleClassi?erSystems(MCS2002),heldattheGrandHotel ChiaLaguna,Cagliari,Italy,onJune24-26,2002. The29papersselectedby thescienti?ccommitteehavebeenorganizedinsessionsdealingwithbagging andboosting,ensemblelearningandneuralnetworks,combinationstrategies, designmethodologies,analysisandperformanceevaluation,andapplications. Theworkshopprogramandthisvolumeareenrichedwiththreeinvitedtalks givenbyJoydeepGhosh(UniversityofTexas,USA),TrevorHastie(Stanford University,USA),andSarunasRaudys(VilniusGediminasTechnicalUniversity, Lithuania). Papersweresubmittedfromresearchersofthefourdiversecom- nities,socon?rmingthatthisseriesofworkshopscanbecomeacommonforum VI Foreword forexchangingviewsandreportinglatestresearchresults. Asfortheprevious editions,thesigni?cantnumberofpapersdealingwithrealpatternrecognition applicationsareproofofthepracticalutilityofmultipleclassi?ersystems. This workshopwassupportedbytheUniversityofCagliari,Italy,theUniversityof Surrey,Guildford,UnitedKingdom,andtheDepartmentofElectricalandEl- tronicEngineeringoftheUniversityofCagliari. Allthesesupportsaregratefully acknowledged. WealsothanktheInternationalAssociationforPatternRecog- tionanditsTechnicalCommitteeTC1onStatisticalPatternRecognitionTe- niquesforsponsoringMCS2002. Wewishtoexpressourappreciationtoallthose whohelpedtoorganizeMCS2002. Firstofall,wewouldliketothankallthe membersoftheScienti?cCommitteewhoseprofess
This book constitutes the refereed proceedings of the Third International Workshop on Multiple Classifier Systems, MCS 2002, held in Cagliari, Italy, in June 2002.
The 29 revised full papers presented together with three invited papers were carefully reviewed and selected for inclusion in the volume. The papers are organized in topical sections on bagging and boosting, ensemble learning and neural networks, design methodologies, combination strategies, analysis and performance evaluation, and applications.
"Sobre este título" puede pertenecer a otra edición de este libro.
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