{"id":"https://openalex.org/W2978910146","doi":"https://doi.org/10.1109/ijcnn.2019.8851856","title":"Analyzing the impact of data representations in classification problems using clustering","display_name":"Analyzing the impact of data representations in classification problems using clustering","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978910146","doi":"https://doi.org/10.1109/ijcnn.2019.8851856","mag":"2978910146"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8851856","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033050828","display_name":"Felipe Farias","orcid":"https://orcid.org/0000-0001-7411-5562"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Felipe Costa Farias","raw_affiliation_strings":["Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife, Brazil"],"affiliations":[{"raw_affiliation_string":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025550530","display_name":"Teresa B. Ludermir","orcid":"https://orcid.org/0000-0002-8980-6742"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Teresa Bernarda Ludermir","raw_affiliation_strings":["Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife, Brazil"],"affiliations":[{"raw_affiliation_string":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028876161","display_name":"Carmelo J. A. Bastos-Filho","orcid":"https://orcid.org/0000-0002-0924-5341"},"institutions":[{"id":"https://openalex.org/I71437568","display_name":"Universidade de Pernambuco","ror":"https://ror.org/00gtcbp88","country_code":"BR","type":"education","lineage":["https://openalex.org/I71437568"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Carmelo J. A. Bastos-Filho Ecomp","raw_affiliation_strings":["Universidade de Pernambuco, Recife, Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade de Pernambuco, Recife, Brazil","institution_ids":["https://openalex.org/I71437568"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034776629","display_name":"Fl\u00e1vio Rosendo da Silva Oliveira","orcid":"https://orcid.org/0000-0002-0665-1950"},"institutions":[{"id":"https://openalex.org/I2800363144","display_name":"Instituto Federal de Educa\u00e7\u00e3o, Ci\u00eancia e Tecnologia de Pernambuco","ror":"https://ror.org/02y7zaj23","country_code":"BR","type":"education","lineage":["https://openalex.org/I1293487690","https://openalex.org/I2800363144","https://openalex.org/I2801200668"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Flavio Rosendo da Silva Oliveira","raw_affiliation_strings":["Instituto Federal de Educa\u00e7\u00e3o, Ci\u00eancia e Tecnologia de Pernambuco, Paulista, Brazil"],"affiliations":[{"raw_affiliation_string":"Instituto Federal de Educa\u00e7\u00e3o, Ci\u00eancia e Tecnologia de Pernambuco, Paulista, Brazil","institution_ids":["https://openalex.org/I2800363144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5033050828"],"corresponding_institution_ids":["https://openalex.org/I25112270"],"apc_list":null,"apc_paid":null,"fwci":0.289,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67384625,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"521","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/silhouette","display_name":"Silhouette","score":0.7414692640304565},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6817049980163574},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.665635347366333},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6559911966323853},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6255823969841003},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5648618340492249},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4957357347011566},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4628443419933319},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4581858217716217},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.4206990599632263},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4161178171634674},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.4108234643936157},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4008515179157257},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.28400278091430664}],"concepts":[{"id":"https://openalex.org/C58103923","wikidata":"https://www.wikidata.org/wiki/Q2286025","display_name":"Silhouette","level":2,"score":0.7414692640304565},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6817049980163574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.665635347366333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6559911966323853},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6255823969841003},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5648618340492249},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4957357347011566},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4628443419933319},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4581858217716217},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.4206990599632263},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4161178171634674},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.4108234643936157},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4008515179157257},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28400278091430664},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8851856","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W141301003","https://openalex.org/W2076063813","https://openalex.org/W2101234009","https://openalex.org/W2122336977","https://openalex.org/W2132920316","https://openalex.org/W2134880336","https://openalex.org/W2138779041","https://openalex.org/W2144323544","https://openalex.org/W2151779862","https://openalex.org/W2153233077","https://openalex.org/W2293057855","https://openalex.org/W2495433026","https://openalex.org/W2752448697","https://openalex.org/W2919115771","https://openalex.org/W6605727015","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W1622964048","https://openalex.org/W30315714","https://openalex.org/W1906975550","https://openalex.org/W1965274140","https://openalex.org/W779885325","https://openalex.org/W2150972844","https://openalex.org/W2393615320","https://openalex.org/W3110435694","https://openalex.org/W2001760863","https://openalex.org/W3101081936"],"abstract_inverted_index":{"This":[0],"work":[1],"presents":[2],"an":[3],"investigation":[4],"about":[5],"how":[6],"to":[7,13,45,62,74],"better":[8],"represent":[9],"output":[10],"data":[11],"labels":[12],"be":[14],"used":[15,41],"in":[16,90,105,112,118],"supervised":[17],"training":[18],"of":[19],"classifiers.":[20],"The":[21],"posed":[22],"hypothesis":[23],"is":[24],"that":[25,89],"grouping":[26],"cohesive":[27],"patterns":[28],"into":[29],"clusters":[30],"and":[31,54,64,108],"assigning":[32],"them":[33],"sub-labels,":[34,81],"may":[35],"improve":[36],"the":[37,52,93,97],"classifier":[38],"performance.":[39],"We":[40],"12":[42],"benchmark":[43],"datasets":[44],"test":[46],"our":[47],"hypothesis.":[48],"First,":[49],"we":[50,87],"create":[51],"clusters,":[53],"when":[55],"appropriate,":[56],"new":[57],"sub-labels":[58,94],"were":[59,72,95],"generated,":[60],"according":[61],"Fuzzy-CMeans":[63],"Silhouette":[65],"score":[66],"thresholds.":[67],"After":[68],"that,":[69],"Multilayer":[70],"Perceptrons":[71],"employed":[73],"model":[75],"each":[76],"dataset":[77],"with":[78,100,103],"cluster":[79],"generated":[80],"obtaining":[82],"promising":[83],"results.":[84],"From":[85],"results,":[86],"observed":[88],"cases":[91,107],"where":[92],"used,":[96],"accuracy":[98],"increased":[99],"statistical":[101],"significance":[102],"p=0.05":[104],"22":[106],"remained":[109],"statistically":[110],"equivalent":[111],"14":[113],"cases,":[114],"presenting":[115],"no":[116],"decrease":[117],"accuracy.":[119]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}
