{"id":"https://openalex.org/W1965319367","doi":"https://doi.org/10.1109/ijcnn.2007.4371330","title":"Random Feature Subset Selection for Analysis of Data with Missing Features","display_name":"Random Feature Subset Selection for Analysis of Data with Missing Features","publication_year":2007,"publication_date":"2007-08-01","ids":{"openalex":"https://openalex.org/W1965319367","doi":"https://doi.org/10.1109/ijcnn.2007.4371330","mag":"1965319367"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2007.4371330","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2007.4371330","pdf_url":null,"source":{"id":"https://openalex.org/S4210195743","display_name":"IEEE International Conference on Neural Networks/IEEE ... International Conference on Neural Networks","issn_l":"1098-7576","issn":["1098-7576","1558-3902"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 International Joint Conference on Neural Networks","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/A5057551137","display_name":"Joseph DePasquale","orcid":"https://orcid.org/0000-0002-9142-9755"},"institutions":[{"id":"https://openalex.org/I44265643","display_name":"Rowan University","ror":"https://ror.org/049v69k10","country_code":"US","type":"education","lineage":["https://openalex.org/I44265643"]},{"id":"https://openalex.org/I4210121626","display_name":"Signal Processing (United States)","ror":"https://ror.org/021gzyw51","country_code":"US","type":"company","lineage":["https://openalex.org/I4210121626"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Joseph DePasquale","raw_affiliation_strings":["Signal Processing and Pattern Recognition Laboratory, Electrical and Computer Engineering, Rowan University, Glassboro, NJ, USA","Rowan Univ., Glassboro#TAB#"],"affiliations":[{"raw_affiliation_string":"Signal Processing and Pattern Recognition Laboratory, Electrical and Computer Engineering, Rowan University, Glassboro, NJ, USA","institution_ids":["https://openalex.org/I44265643","https://openalex.org/I4210121626"]},{"raw_affiliation_string":"Rowan Univ., Glassboro#TAB#","institution_ids":["https://openalex.org/I44265643"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025314990","display_name":"Robi Polikar","orcid":"https://orcid.org/0000-0002-2739-4228"},"institutions":[{"id":"https://openalex.org/I44265643","display_name":"Rowan University","ror":"https://ror.org/049v69k10","country_code":"US","type":"education","lineage":["https://openalex.org/I44265643"]},{"id":"https://openalex.org/I4210121626","display_name":"Signal Processing (United States)","ror":"https://ror.org/021gzyw51","country_code":"US","type":"company","lineage":["https://openalex.org/I4210121626"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robi Polikar","raw_affiliation_strings":["Signal Processing and Pattern Recognition Laboratory, Electrical and Computer Engineering, Rowan University, Glassboro, NJ, USA","Rowan Univ., Glassboro#TAB#"],"affiliations":[{"raw_affiliation_string":"Signal Processing and Pattern Recognition Laboratory, Electrical and Computer Engineering, Rowan University, Glassboro, NJ, USA","institution_ids":["https://openalex.org/I44265643","https://openalex.org/I4210121626"]},{"raw_affiliation_string":"Rowan Univ., Glassboro#TAB#","institution_ids":["https://openalex.org/I44265643"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5057551137"],"corresponding_institution_ids":["https://openalex.org/I4210121626","https://openalex.org/I44265643"],"apc_list":null,"apc_paid":null,"fwci":0.4076,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56619911,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"7","issue":null,"first_page":"2379","last_page":"2384"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9983999729156494,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9983999729156494,"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/T10057","display_name":"Face and Expression Recognition","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9937999844551086,"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/random-subspace-method","display_name":"Random subspace method","score":0.8168745040893555},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.8006754517555237},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.6638221740722656},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6626540422439575},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6226691007614136},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5862637758255005},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5741019248962402},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5380681753158569},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5108723044395447},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.48397159576416016},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4150046408176422},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4133055508136749}],"concepts":[{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.8168745040893555},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.8006754517555237},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.6638221740722656},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6626540422439575},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6226691007614136},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5862637758255005},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5741019248962402},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5380681753158569},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5108723044395447},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.48397159576416016},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4150046408176422},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4133055508136749},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2007.4371330","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2007.4371330","pdf_url":null,"source":{"id":"https://openalex.org/S4210195743","display_name":"IEEE International Conference on Neural Networks/IEEE ... International Conference on Neural Networks","issn_l":"1098-7576","issn":["1098-7576","1558-3902"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 International Joint Conference on Neural Networks","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.387.6451","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.387.6451","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://users.rowan.edu/~polikar/RESEARCH/PUBLICATIONS/ijcnn07b.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6299999952316284}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1985419027","https://openalex.org/W1988790447","https://openalex.org/W2103753221","https://openalex.org/W2113242816","https://openalex.org/W2115986610","https://openalex.org/W2122752936","https://openalex.org/W2128152410","https://openalex.org/W2151092853","https://openalex.org/W2151779605","https://openalex.org/W2161151719","https://openalex.org/W2168118654","https://openalex.org/W3120740533","https://openalex.org/W3134435763","https://openalex.org/W6677144717","https://openalex.org/W6681966656","https://openalex.org/W6682706280"],"related_works":["https://openalex.org/W2007593166","https://openalex.org/W1603777065","https://openalex.org/W2143234973","https://openalex.org/W2397292208","https://openalex.org/W4221136059","https://openalex.org/W1548677759","https://openalex.org/W109131529","https://openalex.org/W1503513760","https://openalex.org/W2073883415","https://openalex.org/W3080944905"],"abstract_inverted_index":{"We":[0,105,167],"discuss":[1],"an":[2,41,59,65],"ensemble-of-classifiers":[3],"based":[4],"algorithm":[5,171],"for":[6],"the":[7,19,27,79,98,102,138,143,146,158,163],"missing":[8,68,81,121,180],"feature":[9,82],"problem.":[10],"The":[11,36],"proposed":[12],"approach":[13],"is":[14,38],"inspired":[15],"in":[16,24,185],"part":[17,25],"by":[18,26,89],"random":[20,53],"subspace":[21],"method,":[22],"and":[23,52,140],"incremental":[28],"learning":[29],"algorithm,":[30],"Learn":[31],"<sup":[32],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[33],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">++</sup>":[34],".":[35],"premise":[37],"to":[39,96,119,130,136,156,176],"generate":[40],"adequately":[42],"large":[43],"number":[44,152],"of":[45,55,101,134,145,153,160,178],"classifiers,":[46],"each":[47],"trained":[48],"on":[49,111,162],"a":[50,91,112,182],"different":[51,132],"combination":[54,94],"features,":[56,69],"drawn":[57],"from":[58],"iteratively":[60],"updated":[61],"distribution.":[62],"To":[63],"classify":[64],"instance":[66],"with":[67],"only":[70],"those":[71],"classifiers":[72,86],"whose":[73],"training":[74],"data":[75],"did":[76],"not":[77],"include":[78,131],"currently":[80],"are":[83,87],"used.":[84],"These":[85],"combined":[88],"using":[90],"majority":[92],"voting":[93],"rule":[95],"obtain":[97],"final":[99],"classification":[100,165],"given":[103],"instance.":[104],"had":[106],"previously":[107],"presented":[108],"preliminary":[109],"results":[110],"similar":[113],"approach,":[114],"which":[115],"could":[116],"handle":[117],"up":[118,175],"10%":[120],"data.":[122],"In":[123],"this":[124,170],"study,":[125],"we":[126],"expand":[127],"our":[128],"work":[129],"types":[133],"rules":[135],"update":[137],"distribution,":[139],"also":[141],"examine":[142],"effect":[144],"algorithm's":[147],"primary":[148],"free":[149],"parameter":[150],"(the":[151],"features":[154,179],"used":[155],"train":[157],"ensemble":[159],"classifiers)":[161],"overall":[164],"performance.":[166,186],"show":[168],"that":[169],"can":[172],"now":[173],"accommodate":[174],"30%":[177],"without":[181],"significant":[183],"drop":[184]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
