Multiple Classifier Systems Third International Workshop, MCS 2002, Cagliari, Italy, June 24-26, 2002. Proceedings

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