000168543 001__ 168543
000168543 005__ 20260225150304.0
000168543 0248_ $$2sideral$$a75621
000168543 0247_ $$2doi$$a10.1016/j.patcog.2006.04.005
000168543 037__ $$aART-2006-75621
000168543 041__ $$aeng
000168543 100__ $$0(orcid)0000-0003-0630-4366$$aLozano, M.$$uUniversidad de Zaragoza
000168543 245__ $$aExperimental study on prototype optimisation algorithms for prototype-based classification in vector spaces
000168543 260__ $$c2006
000168543 5060_ $$aAccess copy available to the general public$$fUnrestricted
000168543 5203_ $$aPrototype-based classification relies on the distances between the examples to be classified and carefully chosen prototypes. A small set of prototypes is of interest to keep the computational complexity low, while maintaining high classification accuracy. An experimental study of some old and new prototype optimisation techniques is presented, in which the prototypes are either selected or generated from the given data. These condensing techniques are evaluated on real data, represented in vector spaces, by comparing their resulting reduction rates and classification performance. Usually the determination of prototypes is studied in relation with the nearest neighbour rule. We will show that the use of more general dissimilarity-based classifiers can be more beneficial. An important point in our study is that the adaptive condensing schemes
here discussed allow the user to choose the number of prototypes freely according to the needs. If such techniques are combined with linear dissimilarity-based classifiers, they provide the best trade-off of small condensed sets and high classification accuracy
000168543 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
000168543 590__ $$a1.822$$b2006
000168543 591__ $$aENGINEERING, ELECTRICAL & ELECTRONIC$$b28 / 205 = 0.137$$c2006$$dQ1$$eT1
000168543 591__ $$aCOMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE$$b18 / 85 = 0.212$$c2006$$dQ1$$eT1
000168543 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/submittedVersion
000168543 700__ $$aSotoca, JM.
000168543 700__ $$aSánchez, JS.
000168543 700__ $$aPla, F.
000168543 700__ $$aPekalska, E.
000168543 700__ $$aDuin, RPW.
000168543 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000168543 773__ $$g39 (2006), 1827-1838$$pPattern recogn.$$tPattern Recognition$$x0031-3203
000168543 8564_ $$s180455$$uhttps://zaguan.unizar.es/record/168543/files/texto_completo.pdf$$yPostprint
000168543 8564_ $$s1638037$$uhttps://zaguan.unizar.es/record/168543/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000168543 909CO $$ooai:zaguan.unizar.es:168543$$particulos$$pdriver
000168543 951__ $$a2026-02-25-14:59:56
000168543 980__ $$aARTICLE