{"id":"https://openalex.org/W2153753536","doi":"https://doi.org/10.1109/cec.2011.5949692","title":"A two-population evolutionary algorithm for feature extraction: Combining filter and wrapper","display_name":"A two-population evolutionary algorithm for feature extraction: Combining filter and wrapper","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W2153753536","doi":"https://doi.org/10.1109/cec.2011.5949692","mag":"2153753536"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2011.5949692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2011.5949692","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Congress of Evolutionary Computation (CEC)","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/A5059868282","display_name":"Eun Yeong Ahn","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Eun Yeong Ahn","raw_affiliation_strings":["Information Sciences and Technology, Pennsylvania State University, University Park, PA, USA"],"affiliations":[{"raw_affiliation_string":"Information Sciences and Technology, Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112631132","display_name":"Tracy Mullen","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tracy Mullen","raw_affiliation_strings":["Information Sciences and Technology, Pennsylvania State University, University Park, PA, USA"],"affiliations":[{"raw_affiliation_string":"Information Sciences and Technology, Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109056901","display_name":"John Yen","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Yen","raw_affiliation_strings":["Information Sciences and Technology, Pennsylvania State University, University Park, PA, USA"],"affiliations":[{"raw_affiliation_string":"Information Sciences and Technology, Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5059868282"],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.14136524,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"736","last_page":"743"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9998000264167786,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9998000264167786,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9988999962806702,"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/T10320","display_name":"Neural Networks and Applications","score":0.9757999777793884,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8237491846084595},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7204903960227966},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6723421812057495},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6193305253982544},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6064552068710327},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.6028674244880676},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5210177898406982},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5156201720237732},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4922453463077545},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4579209089279175},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4555855393409729},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.4194849133491516},{"id":"https://openalex.org/keywords/evolutionary-computation","display_name":"Evolutionary computation","score":0.4131873846054077},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39550191164016724},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3221147656440735},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11690324544906616}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8237491846084595},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7204903960227966},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6723421812057495},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6193305253982544},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6064552068710327},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.6028674244880676},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5210177898406982},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5156201720237732},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4922453463077545},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4579209089279175},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4555855393409729},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.4194849133491516},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.4131873846054077},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39550191164016724},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3221147656440735},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11690324544906616},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cec.2011.5949692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2011.5949692","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Congress of Evolutionary Computation (CEC)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.338.2186","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.338.2186","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1535723299","https://openalex.org/W1542321601","https://openalex.org/W1554944419","https://openalex.org/W1555148682","https://openalex.org/W1560107318","https://openalex.org/W1573534773","https://openalex.org/W1585743408","https://openalex.org/W1603293845","https://openalex.org/W1761022139","https://openalex.org/W1957053378","https://openalex.org/W1973961812","https://openalex.org/W1989540221","https://openalex.org/W2004338242","https://openalex.org/W2008023154","https://openalex.org/W2011209865","https://openalex.org/W2034418625","https://openalex.org/W2050599941","https://openalex.org/W2084812512","https://openalex.org/W2093799708","https://openalex.org/W2109357644","https://openalex.org/W2126957654","https://openalex.org/W2133990480","https://openalex.org/W2135190479","https://openalex.org/W2149624569","https://openalex.org/W2155925556","https://openalex.org/W2171033594","https://openalex.org/W2200804511","https://openalex.org/W3145481521","https://openalex.org/W4207030835","https://openalex.org/W6632459205","https://openalex.org/W6633497745"],"related_works":["https://openalex.org/W4295122168","https://openalex.org/W3155717344","https://openalex.org/W1770458422","https://openalex.org/W4297582752","https://openalex.org/W4285805405","https://openalex.org/W2391924736","https://openalex.org/W3133779647","https://openalex.org/W1560122427","https://openalex.org/W2021957875","https://openalex.org/W2802808995"],"abstract_inverted_index":{"Extracting":[0],"good":[1],"features":[2,20],"is":[3,41,71,85,97,117],"critical":[4],"to":[5,21,28],"the":[6,29,75,81,99,111,119,144,174],"performance":[7],"of":[8,33,37,69,77,114,137],"learning":[9,92],"algorithms":[10,50],"such":[11,47],"as":[12,48],"classifiers.":[13],"Feature":[14],"extraction":[15,164],"selects":[16],"and":[17,35,44,169,172],"transforms":[18],"original":[19],"find":[22],"information":[23],"hidden":[24],"in":[25,139],"data.":[26,150],"Due":[27],"huge":[30],"search":[31,40,46],"space":[32],"selection":[34],"transformation":[36],"features,":[38,70],"exhaustive":[39],"computationally":[42],"prohibitive":[43],"randomized":[45],"evolutionary":[49],"(EA)":[51],"are":[52],"often":[53],"used.":[54],"In":[55],"our":[56,122],"prior":[57],"work":[58],"on":[59,125],"evolutionary-based":[60],"feature":[61,83,163],"extraction,":[62],"an":[63,107],"individual,":[64],"which":[65,96,116],"represents":[66],"a":[67,78,91,126,134,159],"set":[68,84],"evaluated":[72],"by":[73,110],"estimating":[74],"accuracy":[76,146],"classifier":[79],"when":[80],"individual's":[82],"used":[86],"for":[87,147,162],"learning.":[88],"Although":[89],"incorporating":[90],"algorithm":[93],"during":[94],"evaluation,":[95],"called":[98,118],"wrapper":[100,127,170],"approach,":[101],"generally":[102],"performs":[103],"better":[104],"than":[105],"evaluating":[106],"individual":[108],"simply":[109],"statistical":[112],"properties":[113],"data,":[115],"filter":[120,168],"appproach,":[121],"EA":[123,161],"based":[124],"approach":[128],"suffers":[129],"from":[130],"overfitting,":[131],"so":[132],"that":[133,166],"slight":[135],"enhancement":[136],"fitness":[138],"training":[140],"can":[141],"dramatically":[142],"reduce":[143],"classification":[145],"unseen":[148],"testing":[149],"To":[151],"cope":[152],"with":[153],"this":[154,156],"problem,":[155],"paper":[157],"proposes":[158],"two-population":[160],"(TEAFE)":[165],"combines":[167],"approaches,":[171],"shows":[173],"promising":[175],"preliminary":[176],"results.":[177]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}