{"id":"https://openalex.org/W2164808212","doi":"https://doi.org/10.1145/1388969.1389020","title":"Informative sampling for large unbalanced data sets","display_name":"Informative sampling for large unbalanced data sets","publication_year":2008,"publication_date":"2008-07-12","ids":{"openalex":"https://openalex.org/W2164808212","doi":"https://doi.org/10.1145/1388969.1389020","mag":"2164808212"},"language":"en","primary_location":{"id":"doi:10.1145/1388969.1389020","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1388969.1389020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th annual conference companion on Genetic and evolutionary computation","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/A5101457173","display_name":"Zhenyu Lu","orcid":"https://orcid.org/0000-0003-4175-5402"},"institutions":[{"id":"https://openalex.org/I111236770","display_name":"University of Vermont","ror":"https://ror.org/0155zta11","country_code":"US","type":"education","lineage":["https://openalex.org/I111236770"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhenyu Lu","raw_affiliation_strings":["University of Vermont, Burlington, VT, USA"],"affiliations":[{"raw_affiliation_string":"University of Vermont, Burlington, VT, USA","institution_ids":["https://openalex.org/I111236770"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033975434","display_name":"Anand I. Rughani","orcid":null},"institutions":[{"id":"https://openalex.org/I111236770","display_name":"University of Vermont","ror":"https://ror.org/0155zta11","country_code":"US","type":"education","lineage":["https://openalex.org/I111236770"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anand I. Rughani","raw_affiliation_strings":["University of Vermont, Burlington, VT, USA"],"affiliations":[{"raw_affiliation_string":"University of Vermont, Burlington, VT, USA","institution_ids":["https://openalex.org/I111236770"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001453478","display_name":"Bruce I. Tranmer","orcid":null},"institutions":[{"id":"https://openalex.org/I111236770","display_name":"University of Vermont","ror":"https://ror.org/0155zta11","country_code":"US","type":"education","lineage":["https://openalex.org/I111236770"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bruce I. Tranmer","raw_affiliation_strings":["University of Vermont, Burlington, VT, USA"],"affiliations":[{"raw_affiliation_string":"University of Vermont, Burlington, VT, USA","institution_ids":["https://openalex.org/I111236770"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066791342","display_name":"Josh Bongard","orcid":"https://orcid.org/0000-0001-8515-0822"},"institutions":[{"id":"https://openalex.org/I111236770","display_name":"University of Vermont","ror":"https://ror.org/0155zta11","country_code":"US","type":"education","lineage":["https://openalex.org/I111236770"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Josh Bongard","raw_affiliation_strings":["University of Vermont, Burlington, VT, USA"],"affiliations":[{"raw_affiliation_string":"University of Vermont, Burlington, VT, USA","institution_ids":["https://openalex.org/I111236770"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101457173"],"corresponding_institution_ids":["https://openalex.org/I111236770"],"apc_list":null,"apc_paid":null,"fwci":4.6927,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.94791535,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2047","last_page":"2054"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9993000030517578,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9993000030517578,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9853000044822693,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9837999939918518,"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/computer-science","display_name":"Computer science","score":0.7123873233795166},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.664760947227478},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5903509855270386},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5510696172714233},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5424994826316833},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5227782130241394},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5088105797767639},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.49838757514953613},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4850570261478424},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4554356038570404},{"id":"https://openalex.org/keywords/geodetic-datum","display_name":"Geodetic datum","score":0.4433518648147583},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.44293272495269775},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.42204514145851135},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3290623426437378},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3279438018798828}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7123873233795166},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.664760947227478},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5903509855270386},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5510696172714233},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5424994826316833},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5227782130241394},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5088105797767639},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.49838757514953613},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4850570261478424},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4554356038570404},{"id":"https://openalex.org/C58754882","wikidata":"https://www.wikidata.org/wiki/Q1502887","display_name":"Geodetic datum","level":2,"score":0.4433518648147583},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.44293272495269775},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.42204514145851135},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3290623426437378},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3279438018798828},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1388969.1389020","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1388969.1389020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th annual conference companion on Genetic and evolutionary computation","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.152.9261","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.152.9261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.bham.ac.uk/~wbl/biblio/gecco2008/docs/p2047.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.217.1340","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.217.1340","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.uvm.edu/~jbongard/papers/2008_GECCO_Lu.pdf","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":35,"referenced_works":["https://openalex.org/W85350352","https://openalex.org/W129457532","https://openalex.org/W142793689","https://openalex.org/W1504694836","https://openalex.org/W1563088657","https://openalex.org/W1592355944","https://openalex.org/W1593345689","https://openalex.org/W1595740553","https://openalex.org/W1602085661","https://openalex.org/W1603664789","https://openalex.org/W1949548705","https://openalex.org/W1986222379","https://openalex.org/W2001685400","https://openalex.org/W2002366641","https://openalex.org/W2015223144","https://openalex.org/W2021758087","https://openalex.org/W2048828870","https://openalex.org/W2058959574","https://openalex.org/W2060542593","https://openalex.org/W2080021732","https://openalex.org/W2085989833","https://openalex.org/W2105857214","https://openalex.org/W2122410182","https://openalex.org/W2124290836","https://openalex.org/W2125055259","https://openalex.org/W2144315657","https://openalex.org/W2147735646","https://openalex.org/W2158669285","https://openalex.org/W2165166126","https://openalex.org/W2435251607","https://openalex.org/W2620344835","https://openalex.org/W2911740249","https://openalex.org/W2914859268","https://openalex.org/W3010319051","https://openalex.org/W6678191276"],"related_works":["https://openalex.org/W2786391746","https://openalex.org/W4381430104","https://openalex.org/W2995102745","https://openalex.org/W4226059458","https://openalex.org/W2914559142","https://openalex.org/W1990237101","https://openalex.org/W4285322112","https://openalex.org/W3196471634","https://openalex.org/W3128438030","https://openalex.org/W4292794239"],"abstract_inverted_index":{"Selective":[0],"sampling":[1,152],"is":[2,29,57,66,133],"a":[3,50,67,79,84,99],"form":[4],"of":[5,13,78,86,101,175],"active":[6],"learning":[7],"which":[8,56,163],"can":[9],"reduce":[10],"the":[11,22,60,76,90,107,119,127,137,142,145,158,176,182],"cost":[12],"training":[14,23,27,80,108,120,160],"by":[15],"only":[16,88],"drawing":[17],"informative":[18],"data":[19,117,124,150,161],"points":[20],"into":[21],"set.":[24,121],"This":[25],"selected":[26,91,159],"set":[28,85,125],"expected":[30],"to":[31,38,53,74,114,135,181],"contain":[32],"more":[33,46],"information":[34],"for":[35,118,169],"modeling":[36,43,172],"compared":[37],"random":[39],"sampling,":[40,55],"thus":[41],"making":[42],"faster":[44],"and":[45,82,110,151,173],"accurate.":[47],"We":[48],"introduce":[49],"novel":[51],"approach":[52],"selective":[54],"derived":[58],"from":[59,154],"Estimation-Exploration":[61],"Algorithm":[62],"(EEA).":[63],"The":[64,93],"EEA":[65],"coevolutionary":[68],"algorithm":[69,94,143,147],"that":[70,141,178],"uses":[71,111],"model":[72],"disagreement":[73,113],"determine":[75],"significance":[77],"datum,":[81],"evolves":[83],"models":[87],"on":[89,106],"data.":[92,183],"in":[95],"this":[96],"paper":[97],"trains":[98],"population":[100],"Artificial":[102],"Neural":[103],"Networks":[104],"(ANN)":[105],"set,":[109],"their":[112],"seek":[115],"new":[116],"A":[122],"medical":[123],"called":[126],"National":[128],"Trauma":[129],"Data":[130],"Bank":[131],"(NTDB)":[132],"used":[134],"test":[136],"algorithm.":[138],"Experiments":[139],"show":[140],"outperforms":[144],"equivalent":[146],"using":[148],"randomly-selected":[149],"evenly":[153],"each":[155],"class.":[156],"Finally,":[157],"reveals":[162],"features":[164],"most":[165],"affect":[166],"outcome,":[167],"allowing":[168],"both":[170],"improved":[171],"understanding":[174],"processes":[177],"gave":[179],"rise":[180]},"counts_by_year":[{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
