Rede Neural Probabilística para a Classificação de Atividades Econômicas

Abstract

Thisworkpresents anapproach basedonArtificialNeuralNetworksforproblemsofmulti-label classification.In particular,was useda modifiedversionof ProbabilisticNeuralNetworkto handlesuch problems.In experiments carriedoutin variousdatabasesknownin theliterature,theProbabilisticNeuralNetworkproposalpresenteda performancecomparable,andsometimesevensuperiorto otheralgorithmsspecializedin thistype ofproblem.Asthemainfocusof thisworkwas thestudyof strategiesforautomatictextclassi-ficationof economicactivitiesthenwerealsoconductedexperiments usinga databaseofeconomicactivities.However,unlike of databasesusedpreviously, thisdatabaseshowsahugenumber of categoriesandfewsamplesof trainingby category, which increasesthedegreeof difficulty thisproblem.In theexperiments wereusedto ProbabilisticNeuralNetworkproposal,theclassifierMulti-label k-NearestNeighbor anda GeneticAlgorithmforoptimizationof theparameters.Themetricsusedto evaluationof performancehaveshownthattheresultsof ProbabilisticNeuralNetworkweresuperiorandcomparabletotheresultsobtainedby theMulti-label k-NearestNeighbor,showingthattheapproachusedin thisworkis promising.