{"id":"https://openalex.org/W3000969745","doi":"https://doi.org/10.1145/3369114.3369119","title":"Filter-Based Information-Theoretic Feature Selection","display_name":"Filter-Based Information-Theoretic Feature Selection","publication_year":2019,"publication_date":"2019-10-26","ids":{"openalex":"https://openalex.org/W3000969745","doi":"https://doi.org/10.1145/3369114.3369119","mag":"3000969745"},"language":"en","primary_location":{"id":"doi:10.1145/3369114.3369119","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3369114.3369119","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 3rd International Conference on Advances in Artificial Intelligence","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/A5028460841","display_name":"Farinaz Pisheh","orcid":null},"institutions":[{"id":"https://openalex.org/I44461941","display_name":"University of Houston","ror":"https://ror.org/048sx0r50","country_code":"US","type":"education","lineage":["https://openalex.org/I44461941"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Farinaz Pisheh","raw_affiliation_strings":["University of Houston, Houston, TX, USA"],"affiliations":[{"raw_affiliation_string":"University of Houston, Houston, TX, USA","institution_ids":["https://openalex.org/I44461941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034596650","display_name":"Ricardo Vilalta","orcid":"https://orcid.org/0000-0001-8165-8805"},"institutions":[{"id":"https://openalex.org/I44461941","display_name":"University of Houston","ror":"https://ror.org/048sx0r50","country_code":"US","type":"education","lineage":["https://openalex.org/I44461941"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ricardo Vilalta","raw_affiliation_strings":["University of Houston, Houston, TX, USA"],"affiliations":[{"raw_affiliation_string":"University of Houston, Houston, TX, USA","institution_ids":["https://openalex.org/I44461941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5028460841"],"corresponding_institution_ids":["https://openalex.org/I44461941"],"apc_list":null,"apc_paid":null,"fwci":0.3037,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.62218069,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"207","last_page":"211"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9979000091552734,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9979000091552734,"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/T10320","display_name":"Neural Networks and Applications","score":0.9961000084877014,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9959999918937683,"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/feature-selection","display_name":"Feature selection","score":0.7751958966255188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6380031108856201},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.63578861951828},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6169308423995972},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6142852902412415},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5980361700057983},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5440636277198792},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4848569631576538},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4718242585659027},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.46810197830200195},{"id":"https://openalex.org/keywords/minimum-redundancy-feature-selection","display_name":"Minimum redundancy feature selection","score":0.4671812653541565},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.43616676330566406},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.41365987062454224},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3458375930786133},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2866208553314209}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7751958966255188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6380031108856201},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.63578861951828},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6169308423995972},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6142852902412415},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5980361700057983},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5440636277198792},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4848569631576538},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4718242585659027},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.46810197830200195},{"id":"https://openalex.org/C16811321","wikidata":"https://www.wikidata.org/wiki/Q17138905","display_name":"Minimum redundancy feature selection","level":3,"score":0.4671812653541565},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.43616676330566406},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.41365987062454224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3458375930786133},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2866208553314209},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3369114.3369119","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3369114.3369119","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 3rd International Conference on Advances in Artificial Intelligence","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":22,"referenced_works":["https://openalex.org/W398859631","https://openalex.org/W1585743408","https://openalex.org/W1619226191","https://openalex.org/W1661871015","https://openalex.org/W1983575673","https://openalex.org/W1995875735","https://openalex.org/W2015932775","https://openalex.org/W2078093994","https://openalex.org/W2099111195","https://openalex.org/W2148830179","https://openalex.org/W2156504490","https://openalex.org/W2156571267","https://openalex.org/W2210387432","https://openalex.org/W2552399396","https://openalex.org/W2613712744","https://openalex.org/W2808342115","https://openalex.org/W2918032458","https://openalex.org/W2997674406","https://openalex.org/W4285719527","https://openalex.org/W6606712637","https://openalex.org/W6674851815","https://openalex.org/W7066667914"],"related_works":["https://openalex.org/W2286904880","https://openalex.org/W4312247183","https://openalex.org/W2159220931","https://openalex.org/W3046882970","https://openalex.org/W2374344280","https://openalex.org/W4304208879","https://openalex.org/W2385233088","https://openalex.org/W2061500280","https://openalex.org/W4324137389","https://openalex.org/W4295514622"],"abstract_inverted_index":{"Feature":[0],"subset":[1,9,36],"selection":[2,49,110],"methods":[3,50],"aim":[4],"at":[5,66],"identifying":[6],"the":[7,18,22,41,67,99],"smallest":[8],"of":[10,21,37,47,101],"features":[11,38],"that":[12,80],"maximize":[13],"generalization":[14],"performance,":[15],"while":[16],"preserving":[17],"true":[19],"nature":[20],"joint":[23],"data":[24],"distribution.":[25,70],"In":[26,71],"classification":[27],"tasks,":[28],"this":[29,72],"is":[30,81],"tantamount":[31],"to":[32,40,55,90,106],"finding":[33],"an":[34,87],"optimal":[35],"relevant":[39,57,92],"target":[42],"class.":[43],"A":[44],"distinctive":[45],"family":[46],"feature":[48,62,109],"use":[51],"a":[52,77],"distance":[53],"metric":[54,89],"identify":[56],"features,":[58],"even":[59],"under":[60],"high":[61],"interaction,":[63],"by":[64,83],"looking":[65],"local":[68],"class":[69],"study":[73],"we":[74],"present":[75],"EBFS:":[76],"new":[78],"algorithm":[79],"inspired":[82],"Relieff":[84],"and":[85],"uses":[86],"entropy-based":[88],"discover":[91],"features.":[93],"Results":[94],"on":[95],"UCI":[96],"data-sets":[97],"show":[98],"effectiveness":[100],"our":[102],"approach":[103],"when":[104],"compared":[105],"other":[107],"filter-based":[108],"methods.":[111]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
