{"id":"https://openalex.org/W2082083863","doi":"https://doi.org/10.1016/s0950-7051(01)00154-x","title":"Clustered linear regression","display_name":"Clustered linear regression","publication_year":2002,"publication_date":"2002-03-01","ids":{"openalex":"https://openalex.org/W2082083863","doi":"https://doi.org/10.1016/s0950-7051(01)00154-x","mag":"2082083863"},"language":"en","primary_location":{"id":"doi:10.1016/s0950-7051(01)00154-x","is_oa":true,"landing_page_url":"https://doi.org/10.1016/s0950-7051(01)00154-x","pdf_url":"https://www.sciencedirect.com/science/article/pii/S095070510100154X","source":{"id":"https://openalex.org/S10169007","display_name":"Knowledge-Based Systems","issn_l":"0950-7051","issn":["0950-7051","1872-7409"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge-Based Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.sciencedirect.com/science/article/pii/S095070510100154X","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025566591","display_name":"Bertan Ari","orcid":null},"institutions":[{"id":"https://openalex.org/I4210155201","display_name":"Redmond Fire Department","ror":"https://ror.org/05d788x61","country_code":"US","type":"government","lineage":["https://openalex.org/I4210155201"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bertan Ari","raw_affiliation_strings":["16021 NE 36th WAY, Redmond, WA 98052, USA","Redmond, WA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"16021 NE 36th WAY, Redmond, WA 98052, USA","institution_ids":[]},{"raw_affiliation_string":"Redmond, WA#TAB#","institution_ids":["https://openalex.org/I4210155201"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088849430","display_name":"H. Altay G\u00fcvenir","orcid":"https://orcid.org/0000-0003-2589-316X"},"institutions":[{"id":"https://openalex.org/I168864056","display_name":"Bilkent University","ror":"https://ror.org/02vh8a032","country_code":"TR","type":"education","lineage":["https://openalex.org/I168864056"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"H.Altay G\u00fcvenir","raw_affiliation_strings":["Department of Computer Engineering, Bilkent University, Ankara 06533, Turkey","Department of Computer Engineering Bilkent University  Ankara Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Bilkent University, Ankara 06533, Turkey","institution_ids":["https://openalex.org/I168864056"]},{"raw_affiliation_string":"Department of Computer Engineering Bilkent University  Ankara Turkey","institution_ids":["https://openalex.org/I168864056"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5088849430"],"corresponding_institution_ids":["https://openalex.org/I168864056"],"apc_list":{"value":3430,"currency":"USD","value_usd":3430},"apc_paid":null,"fwci":0.6372,"has_fulltext":true,"cited_by_count":47,"citation_normalized_percentile":{"value":0.75947754,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"15","issue":"3","first_page":"169","last_page":"175"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9991000294685364,"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":0.9991000294685364,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9977999925613403,"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":0.9968000054359436,"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/linear-subspace","display_name":"Linear subspace","score":0.918055534362793},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7859045267105103},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7319649457931519},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.6240183711051941},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.49314969778060913},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.48814043402671814},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4856909215450287},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46395817399024963},{"id":"https://openalex.org/keywords/linear-approximation","display_name":"Linear approximation","score":0.462808758020401},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4442235827445984},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.4407292306423187},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42745086550712585},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.41201508045196533},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3636391758918762},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.31997740268707275},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25754857063293457},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15256792306900024},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.08799612522125244}],"concepts":[{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.918055534362793},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7859045267105103},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7319649457931519},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.6240183711051941},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.49314969778060913},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.48814043402671814},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4856909215450287},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46395817399024963},{"id":"https://openalex.org/C160824197","wikidata":"https://www.wikidata.org/wiki/Q2071054","display_name":"Linear approximation","level":3,"score":0.462808758020401},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4442235827445984},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.4407292306423187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42745086550712585},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.41201508045196533},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3636391758918762},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31997740268707275},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25754857063293457},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15256792306900024},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.08799612522125244},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1016/s0950-7051(01)00154-x","is_oa":true,"landing_page_url":"https://doi.org/10.1016/s0950-7051(01)00154-x","pdf_url":"https://www.sciencedirect.com/science/article/pii/S095070510100154X","source":{"id":"https://openalex.org/S10169007","display_name":"Knowledge-Based Systems","issn_l":"0950-7051","issn":["0950-7051","1872-7409"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge-Based Systems","raw_type":"journal-article"},{"id":"pmh:oai:repository.bilkent.edu.tr:11693/10960","is_oa":false,"landing_page_url":"http://hdl.handle.net/11693/10960","pdf_url":null,"source":{"id":"https://openalex.org/S4306400079","display_name":"Bilkent University Institutional Repository (Bilkent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I168864056","host_organization_name":"Bilkent University","host_organization_lineage":["https://openalex.org/I168864056"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Knowledge-Based Systems","raw_type":"Article"},{"id":"pmh:oai:repository.bilkent.edu.tr:11693/24733","is_oa":false,"landing_page_url":"http://hdl.handle.net/11693/24733","pdf_url":null,"source":{"id":"https://openalex.org/S4306400079","display_name":"Bilkent University Institutional Repository (Bilkent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I168864056","host_organization_name":"Bilkent University","host_organization_lineage":["https://openalex.org/I168864056"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Knowledge-Based Systems","raw_type":"Article"}],"best_oa_location":{"id":"doi:10.1016/s0950-7051(01)00154-x","is_oa":true,"landing_page_url":"https://doi.org/10.1016/s0950-7051(01)00154-x","pdf_url":"https://www.sciencedirect.com/science/article/pii/S095070510100154X","source":{"id":"https://openalex.org/S10169007","display_name":"Knowledge-Based Systems","issn_l":"0950-7051","issn":["0950-7051","1872-7409"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge-Based Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2082083863.pdf","grobid_xml":"https://content.openalex.org/works/W2082083863.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W148291325","https://openalex.org/W1527338945","https://openalex.org/W1571076699","https://openalex.org/W1689445748","https://openalex.org/W1986241547","https://openalex.org/W2079917809","https://openalex.org/W2091886411","https://openalex.org/W2102201073","https://openalex.org/W2147169507","https://openalex.org/W2330820318","https://openalex.org/W3085162807","https://openalex.org/W4240861491","https://openalex.org/W4244238212","https://openalex.org/W6851894845"],"related_works":["https://openalex.org/W3100286349","https://openalex.org/W2896134808","https://openalex.org/W3172436493","https://openalex.org/W4287164812","https://openalex.org/W2957492749","https://openalex.org/W1887135636","https://openalex.org/W4289378085","https://openalex.org/W2386063599","https://openalex.org/W1975884855","https://openalex.org/W3213150849"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
