{"id":"https://openalex.org/W2895560478","doi":"https://doi.org/10.1109/access.2018.2873634","title":"A New Filter Feature Selection Based on Criteria Fusion for Gene Microarray Data","display_name":"A New Filter Feature Selection Based on Criteria Fusion for Gene Microarray Data","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2895560478","doi":"https://doi.org/10.1109/access.2018.2873634","mag":"2895560478"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2873634","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2873634","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2873634","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007700207","display_name":"Wenjun Ke","orcid":"https://orcid.org/0000-0002-8836-3257"},"institutions":[{"id":"https://openalex.org/I148128674","display_name":"University of Shanghai for Science and Technology","ror":"https://ror.org/00ay9v204","country_code":"CN","type":"education","lineage":["https://openalex.org/I148128674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjun Ke","raw_affiliation_strings":["School of Optical Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Optical Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I148128674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102960994","display_name":"Chunxue Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I148128674","display_name":"University of Shanghai for Science and Technology","ror":"https://ror.org/00ay9v204","country_code":"CN","type":"education","lineage":["https://openalex.org/I148128674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunxue Wu","raw_affiliation_strings":["School of Optical Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-4938-4570","affiliations":[{"raw_affiliation_string":"School of Optical Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I148128674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054326756","display_name":"Yan Wu","orcid":"https://orcid.org/0000-0001-7876-261X"},"institutions":[{"id":"https://openalex.org/I4210119109","display_name":"Indiana University Bloomington","ror":"https://ror.org/02k40bc56","country_code":"US","type":"education","lineage":["https://openalex.org/I4210119109","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Wu","raw_affiliation_strings":["School of Public and Environmental Affairs, Indiana University Bloomington, Bloomington, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Public and Environmental Affairs, Indiana University Bloomington, Bloomington, IN, USA","institution_ids":["https://openalex.org/I4210119109"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103216531","display_name":"Naixue Xiong","orcid":"https://orcid.org/0000-0002-0394-4635"},"institutions":[{"id":"https://openalex.org/I192664086","display_name":"Northeastern State University","ror":"https://ror.org/01z7kzb45","country_code":"US","type":"education","lineage":["https://openalex.org/I192664086"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neal N. Xiong","raw_affiliation_strings":["Department of Mathematics and Computer Science, Northeastern State University Tahlequah, Tahlequah, OK, USA"],"raw_orcid":"https://orcid.org/0000-0002-0394-4635","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, Northeastern State University Tahlequah, Tahlequah, OK, USA","institution_ids":["https://openalex.org/I192664086"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.0413,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.87613521,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"6","issue":null,"first_page":"61065","last_page":"61076"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9876000285148621,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.765540599822998},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7624148726463318},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6649755239486694},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5746784806251526},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.570872962474823},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5603123307228088},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.541313886642456},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.500507116317749},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.49536240100860596},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4914048910140991},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49060383439064026},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.4684614837169647},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4444272518157959},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.44356441497802734},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4355214238166809},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.412159264087677}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.765540599822998},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7624148726463318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6649755239486694},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5746784806251526},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.570872962474823},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5603123307228088},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.541313886642456},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.500507116317749},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.49536240100860596},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4914048910140991},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49060383439064026},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.4684614837169647},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4444272518157959},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.44356441497802734},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4355214238166809},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.412159264087677},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2873634","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2873634","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f1970f67447e4fb69de01e9b4da09d72","is_oa":false,"landing_page_url":"https://doaj.org/article/f1970f67447e4fb69de01e9b4da09d72","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 61065-61076 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2873634","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2873634","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7699999809265137,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G308111626","display_name":null,"funder_award_id":"61502220","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W104074713","https://openalex.org/W592780493","https://openalex.org/W1485955713","https://openalex.org/W1500895378","https://openalex.org/W1534477342","https://openalex.org/W1661871015","https://openalex.org/W1685464609","https://openalex.org/W1727290854","https://openalex.org/W1808644423","https://openalex.org/W1964042173","https://openalex.org/W1989540221","https://openalex.org/W2069321575","https://openalex.org/W2087684630","https://openalex.org/W2095594899","https://openalex.org/W2100114754","https://openalex.org/W2109363337","https://openalex.org/W2110708978","https://openalex.org/W2113890143","https://openalex.org/W2114060717","https://openalex.org/W2118561568","https://openalex.org/W2119387367","https://openalex.org/W2122210511","https://openalex.org/W2126668662","https://openalex.org/W2143043751","https://openalex.org/W2143347324","https://openalex.org/W2149461695","https://openalex.org/W2149620660","https://openalex.org/W2149772057","https://openalex.org/W2149775297","https://openalex.org/W2154053567","https://openalex.org/W2154560360","https://openalex.org/W2156483112","https://openalex.org/W2156504490","https://openalex.org/W2156571267","https://openalex.org/W2159400887","https://openalex.org/W2163246541","https://openalex.org/W2165580920","https://openalex.org/W2165999916","https://openalex.org/W2313084042","https://openalex.org/W2335170513","https://openalex.org/W2344681634","https://openalex.org/W2510343914","https://openalex.org/W2560046788","https://openalex.org/W2565847703","https://openalex.org/W2581572661","https://openalex.org/W2590822257","https://openalex.org/W2736076499","https://openalex.org/W2787022463","https://openalex.org/W2794316962","https://openalex.org/W2963951026","https://openalex.org/W3105524694","https://openalex.org/W6604230859","https://openalex.org/W6636914306","https://openalex.org/W6637461618","https://openalex.org/W6638249342","https://openalex.org/W6676383760","https://openalex.org/W6681822384","https://openalex.org/W6682686508","https://openalex.org/W6682904970"],"related_works":["https://openalex.org/W2114217318","https://openalex.org/W2794812819","https://openalex.org/W2120164251","https://openalex.org/W2587881214","https://openalex.org/W3104072235","https://openalex.org/W3036945320","https://openalex.org/W2370263288","https://openalex.org/W2989490741","https://openalex.org/W2169311637","https://openalex.org/W2395040056"],"abstract_inverted_index":{"In":[0,82],"machine":[1],"learning":[2],"and":[3,13,37,56,60,98,123,128,144,168],"data":[4,46,121,126],"mining,":[5],"feature":[6,15,20,89,136],"selection":[7,90,137],"aims":[8,101],"to":[9,30,66,76,146,159,176],"seek":[10],"a":[11,27,68,85,173],"compact":[12,69],"discriminant":[14],"subset":[16],"from":[17],"the":[18,32,49,77,80,104,108,148,165],"original":[19],"space.":[21],"It":[22],"is":[23,93,114,157],"usually":[24],"used":[25,171],"as":[26,172],"preprocessing":[28,174],"step":[29],"improve":[31],"prediction":[33,105],"performance,":[34],"understandability,":[35],"scalability,":[36],"generalization":[38],"capability":[39],"of":[40,51,71,79,107,150],"classifiers.":[41],"A":[42],"typical":[43],"gene":[44,119],"microarray":[45,120],"set":[47,70],"has":[48],"characteristics":[50,62],"high":[52],"dimensionality,":[53],"limited":[54],"samples,":[55],"most":[57],"irrelevant":[58],"features,":[59],"these":[61],"make":[63],"it":[64,129],"difficult":[65],"discover":[67],"features":[72,163],"that":[73,155],"really":[74],"contribute":[75],"response":[78],"model.":[81,110],"this":[83,99],"paper,":[84],"score-based":[86],"criteria":[87],"fusion":[88],"method":[91,100,113],"(SCF)":[92],"proposed":[94],"for":[95],"cancer":[96],"prediction,":[97],"at":[102],"improving":[103],"performance":[106,132],"classification":[109],"The":[111],"SCF":[112,156],"evaluated":[115],"on":[116],"five":[117],"open":[118],"sets":[122],"three":[124],"low-dimensional":[125],"sets,":[127],"shows":[130],"superior":[131],"over":[133],"many":[134],"well-known":[135],"methods":[138,167,180],"when":[139],"employing":[140],"two":[141],"classifiers":[142],"SVM":[143],"KNN":[145],"measure":[147],"quality":[149],"selected":[151],"features.":[152],"Experiments":[153],"verify":[154],"able":[158],"find":[160],"more":[161],"discriminative":[162],"than":[164],"competing":[166],"can":[169],"be":[170],"algorithm":[175],"combine":[177],"with":[178],"other":[179],"effectively.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
