{"id":"https://openalex.org/W2968571381","doi":"https://doi.org/10.5220/0007932802670274","title":"Ensemble Learning based on Regressor Chains: A Case on Quality Prediction","display_name":"Ensemble Learning based on Regressor Chains: A Case on Quality Prediction","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2968571381","doi":"https://doi.org/10.5220/0007932802670274","mag":"2968571381"},"language":"en","primary_location":{"id":"doi:10.5220/0007932802670274","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0007932802670274","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Data Science, Technology and Applications","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0007932802670274","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067081563","display_name":"Kenan Cem Demirel","orcid":"https://orcid.org/0000-0002-5398-378X"},"institutions":[{"id":"https://openalex.org/I44925452","display_name":"\u00d6zye\u011fin University","ror":"https://ror.org/01jjhfr75","country_code":"TR","type":"education","lineage":["https://openalex.org/I44925452"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Kenan Demirel","raw_affiliation_strings":["Department of Industrial Engineering, \u00d6zye\u011fin University, Istanbul, 34794 and Turkey, --- Select a Country ---"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, \u00d6zye\u011fin University, Istanbul, 34794 and Turkey, --- Select a Country ---","institution_ids":["https://openalex.org/I44925452"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101522224","display_name":"Ahmet \u015eahin","orcid":"https://orcid.org/0000-0002-9223-3420"},"institutions":[{"id":"https://openalex.org/I44925452","display_name":"\u00d6zye\u011fin University","ror":"https://ror.org/01jjhfr75","country_code":"TR","type":"education","lineage":["https://openalex.org/I44925452"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Ahmet \u015eahin","raw_affiliation_strings":["Department of Industrial Engineering, \u00d6zye\u011fin University, Istanbul, 34794 and Turkey, --- Select a Country ---"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, \u00d6zye\u011fin University, Istanbul, 34794 and Turkey, --- Select a Country ---","institution_ids":["https://openalex.org/I44925452"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081838899","display_name":"Erin\u00e7 Albey","orcid":"https://orcid.org/0000-0001-5004-0578"},"institutions":[{"id":"https://openalex.org/I44925452","display_name":"\u00d6zye\u011fin University","ror":"https://ror.org/01jjhfr75","country_code":"TR","type":"education","lineage":["https://openalex.org/I44925452"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Erinc Albey","raw_affiliation_strings":["Department of Industrial Engineering, \u00d6zye\u011fin University, Istanbul, 34794 and Turkey, --- Select a Country ---"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, \u00d6zye\u011fin University, Istanbul, 34794 and Turkey, --- Select a Country ---","institution_ids":["https://openalex.org/I44925452"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I44925452"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.0892205,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"267","last_page":"274"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.5411999821662903,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.5411999821662903,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.511900007724762,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12384","display_name":"Customer churn and segmentation","score":0.4885999858379364,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6908013224601746},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6265772581100464},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5788662433624268},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48904141783714294},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43656644225120544}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6908013224601746},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6265772581100464},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5788662433624268},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48904141783714294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43656644225120544},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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:10.5220/0007932802670274","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0007932802670274","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Data Science, Technology and Applications","raw_type":"proceedings-article"},{"id":"pmh:oai:eresearch.ozyegin.edu.tr:10679/9294","is_oa":false,"landing_page_url":"http://hdl.handle.net/10679/9294","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conferenceObject"}],"best_oa_location":{"id":"doi:10.5220/0007932802670274","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0007932802670274","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Data Science, Technology and Applications","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"In":[0,112],"this":[1],"study":[2],"we":[3],"construct":[4],"a":[5,16],"prediction":[6,60,119],"model,":[7],"which":[8],"utilizes":[9],"the":[10,21,25,49,59,83,102,105,118],"production":[11],"process":[12],"parameters":[13],"acquired":[14],"from":[15],"textile":[17],"machine":[18,29],"and":[19,38,73,80,129],"predicts":[20],"quality":[22],"characteristics":[23],"of":[24,51,82],"final":[26],"yarn.":[27],"Several":[28],"learning":[30],"algorithms":[31,84],"(decision":[32],"tree,":[33],"multivariate":[34],"adaptive":[35],"regression":[36],"splines":[37],"random":[39],"forest)":[40],"are":[41,85],"used":[42],"for":[43,87,101],"prediction.":[44],"An":[45],"ensemble":[46,95,115],"method,":[47,79],"using":[48,75],"idea":[50,96],"regressor":[52],"chains,":[53],"is":[54,64,92,108],"developed":[55],"to":[56],"further":[57],"improve":[58],"performance.":[61],"Collected":[62],"data":[63,107],"first":[65],"segmented":[66],"into":[67],"two":[68],"parts":[69],"(labeled":[70],"as":[71,110],"\u201cnormal\u201d":[72],"\u201cunusual\u201d)":[74],"local":[76],"outlier":[77],"factor":[78],"performance":[81],"tested":[86],"each":[88],"segment":[89],"separately.":[90],"It":[91],"seen":[93],"that":[94],"proves":[97],"its":[98],"competence":[99],"especially":[100],"cases":[103,114],"where":[104],"collected":[106],"categorized":[109],"unusual.":[111],"such":[113],"algorithm":[116],"improves":[117],"accuracy":[120],"significantly.":[121],"Copyright":[122],"\u00a9":[123],"2019":[124],"by":[125],"SCITEPRESS":[126],"\u2013":[127],"Science":[128],"Technology":[130],"Publications,":[131],"Lda.":[132],"All":[133],"rights":[134],"reserved":[135]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}