{"id":"https://openalex.org/W3004249283","doi":"https://doi.org/10.1109/ieem44572.2019.8978843","title":"Hierarchical Classification and Regression with Feature Selection","display_name":"Hierarchical Classification and Regression with Feature Selection","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3004249283","doi":"https://doi.org/10.1109/ieem44572.2019.8978843","mag":"3004249283"},"language":"en","primary_location":{"id":"doi:10.1109/ieem44572.2019.8978843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem44572.2019.8978843","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","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/A5110316157","display_name":"Shih\u2010Wen Ke","orcid":null},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Shih-Wen Ke","raw_affiliation_strings":["National Central University,Department of Information Management,Taoyuan,Taiwan, R.O.C","Department of Information Management, National Central University, Taoyuan, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"National Central University,Department of Information Management,Taoyuan,Taiwan, R.O.C","institution_ids":["https://openalex.org/I22265921"]},{"raw_affiliation_string":"Department of Information Management, National Central University, Taoyuan, Taiwan, R.O.C","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031063002","display_name":"Chi\u2010Wei Yeh","orcid":null},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chi-Wei Yeh","raw_affiliation_strings":["National Central University,Department of Information Management,Taoyuan,Taiwan, R.O.C","Department of Information Management, National Central University, Taoyuan, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"National Central University,Department of Information Management,Taoyuan,Taiwan, R.O.C","institution_ids":["https://openalex.org/I22265921"]},{"raw_affiliation_string":"Department of Information Management, National Central University, Taoyuan, Taiwan, R.O.C","institution_ids":["https://openalex.org/I22265921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5110316157"],"corresponding_institution_ids":["https://openalex.org/I22265921"],"apc_list":null,"apc_paid":null,"fwci":0.14,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.59966707,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1150","last_page":"1154"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9987999796867371,"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":0.9987999796867371,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9986000061035156,"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":0.9976999759674072,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7487180233001709},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6961657404899597},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.616671621799469},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5868854522705078},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5641278028488159},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5559471249580383},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5097796320915222},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49612030386924744},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4832502007484436},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4509338140487671},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4470858871936798},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3933383822441101},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39091944694519043},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24147731065750122},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21177908778190613},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.062138497829437256}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7487180233001709},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6961657404899597},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.616671621799469},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5868854522705078},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5641278028488159},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5559471249580383},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5097796320915222},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49612030386924744},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4832502007484436},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4509338140487671},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4470858871936798},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3933383822441101},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39091944694519043},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24147731065750122},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21177908778190613},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.062138497829437256},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieem44572.2019.8978843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem44572.2019.8978843","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","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":27,"referenced_works":["https://openalex.org/W1552681844","https://openalex.org/W1964357740","https://openalex.org/W1964494592","https://openalex.org/W1970968805","https://openalex.org/W1976688431","https://openalex.org/W1987281309","https://openalex.org/W1994708707","https://openalex.org/W2002917851","https://openalex.org/W2034562813","https://openalex.org/W2040647667","https://openalex.org/W2063862666","https://openalex.org/W2066793765","https://openalex.org/W2101641917","https://openalex.org/W2117225622","https://openalex.org/W2131595827","https://openalex.org/W2148603752","https://openalex.org/W2149772057","https://openalex.org/W2156516474","https://openalex.org/W2160824456","https://openalex.org/W2170493694","https://openalex.org/W2502759836","https://openalex.org/W2563092004","https://openalex.org/W4205687621","https://openalex.org/W6641163509","https://openalex.org/W6651210516","https://openalex.org/W6677731448","https://openalex.org/W6682933604"],"related_works":["https://openalex.org/W2610868774","https://openalex.org/W4399767649","https://openalex.org/W2092994918","https://openalex.org/W3216594821","https://openalex.org/W2390006526","https://openalex.org/W31220157","https://openalex.org/W3215700490","https://openalex.org/W1915333409","https://openalex.org/W2393341384","https://openalex.org/W2312753042"],"abstract_inverted_index":{"Previous":[0],"studies":[1],"proposed":[2,32,68],"different":[3,106],"hierarchical":[4,23,34,73],"estimation":[5,19,49,60],"approaches":[6],"for":[7,36],"solving":[8],"certain":[9],"specific":[10],"domain":[11],"problems.":[12],"They":[13],"usually":[14],"combine":[15],"two":[16],"or":[17],"more":[18],"models":[20],"in":[21,26],"a":[22,33,71],"fashion.":[24],"Therefore,":[25],"our":[27],"previous":[28],"work":[29],"[2],":[30],"we":[31,76,104],"approach":[35,54],"generic":[37,72],"purposes,":[38],"the":[39,64,67,81,90,97,102,125,134,142,149],"Hierarchical":[40],"Classification":[41],"and":[42,48],"Regression":[43],"(HCR),":[44],"that":[45,124],"incorporates":[46],"classification":[47],"techniques.":[50],"The":[51,121],"HCR":[52,69,82,126],"[2]":[53],"significantly":[55,131],"outperformed":[56],"three":[57],"benchmark":[58],"flat":[59],"models.":[61],"Having":[62],"seen":[63],"potential":[65],"of":[66,99,108,118,148],"as":[70],"regression":[74,129],"scheme,":[75],"propose":[77],"to":[78,89,94,116],"further":[79],"improve":[80],"by":[83],"introducing":[84],"feature":[85,112,138],"selection":[86,113,139],"(FS)":[87],"techniques":[88],"HCR.":[91],"In":[92],"order":[93],"thoroughly":[95],"investigate":[96],"effect":[98],"FS":[100],"on":[101],"HCR,":[103],"examine":[105],"numbers":[107],"attributes":[109],"remained":[110],"after":[111],"with":[114,127,145],"respect":[115],"datasets":[117],"various":[119],"sizes.":[120],"results":[122],"showed":[123],"linear":[128],"performed":[130],"better":[132],"than":[133],"other":[135],"HCRs":[136],"while":[137],"helped":[140],"lower":[141],"RMSE":[143],"slightly":[144],"only":[146],"50%":[147],"original":[150],"features.":[151]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}