{"id":"https://openalex.org/W202987616","doi":null,"title":"Bayes classification of imprecise information of interval type","display_name":"Bayes classification of imprecise information of interval type","publication_year":2011,"publication_date":"2011-01-01","ids":{"openalex":"https://openalex.org/W202987616","mag":"202987616"},"language":"en","primary_location":{"id":"mag:202987616","doi":null,"is_oa":false,"landing_page_url":"http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.baztech-article-BAT5-0070-0007","pdf_url":null,"source":{"id":"https://openalex.org/S31609097","display_name":"Control and Cybernetics","issn_l":"0324-8569","issn":["0324-8569","2720-4278"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","jufo-1","norway-1","poland-40","russia-white-list-4"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Control and Cybernetics","raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5072696337","display_name":"Piotr Kulczycki","orcid":"https://orcid.org/0000-0001-8641-8886","observed_orcids":["https://orcid.org/0000-0001-8641-8886"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Piotr Kulczycki","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8641-8886","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5103129777","display_name":"Piotr Andrzej Kowalski","orcid":"https://orcid.org/0000-0003-4041-6900","observed_orcids":["https://orcid.org/0000-0003-4041-6900"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Piotr A. Kowalski","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4041-6900","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.2017,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.9705202,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":"40","issue":"1","first_page":"101","last_page":"123"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.23319999873638153,"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"}},"topics":[{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.23319999873638153,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.20010000467300415,"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/T10320","display_name":"Neural Networks and Applications","score":0.06849999725818634,"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/bayesian-classification","display_name":"Bayesian classification","score":0.9520000219345093},{"id":"https://openalex.org/keywords/interval-valued-data","display_name":"interval data","score":0.7820000052452087},{"id":"https://openalex.org/keywords/imprecise-data","display_name":"imprecise data","score":0.9409999847412109},{"id":"https://openalex.org/keywords/sensitivity-analysis","display_name":"sensitivity analysis","score":0.6959999799728394},{"id":"https://openalex.org/keywords/multidimensional-classification","display_name":"multidimensional classification","score":0.6230000257492065}],"concepts":[{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.5424931049346924},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.531091570854187},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.49810338020324707},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4795796275138855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47389689087867737},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46050095558166504},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.44038957357406616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4315303862094879},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4192306399345398},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38382941484451294},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.20322036743164062}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:202987616","doi":null,"is_oa":false,"landing_page_url":"http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.baztech-article-BAT5-0070-0007","pdf_url":null,"source":{"id":"https://openalex.org/S31609097","display_name":"Control and Cybernetics","issn_l":"0324-8569","issn":["0324-8569","2720-4278"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","jufo-1","norway-1","poland-40","russia-white-list-4"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Control and Cybernetics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W5410279","https://openalex.org/W1481216622","https://openalex.org/W1522200330","https://openalex.org/W1531857721","https://openalex.org/W1544118023","https://openalex.org/W1562048304","https://openalex.org/W1564947197","https://openalex.org/W1587436835","https://openalex.org/W1898259180","https://openalex.org/W1964136760","https://openalex.org/W2053519393","https://openalex.org/W2060924166","https://openalex.org/W2069100897","https://openalex.org/W2115726234","https://openalex.org/W2117812871","https://openalex.org/W2120176508","https://openalex.org/W2123224804","https://openalex.org/W2127828425","https://openalex.org/W2129476886","https://openalex.org/W2129905273","https://openalex.org/W2134616230","https://openalex.org/W2145937819","https://openalex.org/W2483775066","https://openalex.org/W2586748964","https://openalex.org/W2615478764","https://openalex.org/W2799061466","https://openalex.org/W3142229452"],"related_works":["https://openalex.org/W2184846346","https://openalex.org/W2028225346","https://openalex.org/W2296881779","https://openalex.org/W214771495","https://openalex.org/W2168670188","https://openalex.org/W2130868357","https://openalex.org/W7097576110","https://openalex.org/W1537837137","https://openalex.org/W137116491","https://openalex.org/W2065179158"],"abstract_inverted_index":{"The":[0,71,132],"subject":[1],"of":[2,10,14,20,48,55,67,88,95,100,117,128,134,153],"the":[3,33,43,49,65,76,81,86,98,126,158],"investigation":[4],"presented":[5,160],"here":[6,161],"is":[7,78],"Bayes":[8],"classification":[9,68],"imprecise":[11],"multidimensional":[12],"information":[13],"in-":[15],"terval":[16],"type":[17],"by":[18],"means":[19],"patterns":[21],"defined":[22],"through":[23],"precise":[24],"data,":[25,143],"e.g.":[26],"deterministic":[27],"or":[28,61],"sharp.":[29],"For":[30],"this":[31,96],"purpose":[32],"statistical":[34],"kernel":[35],"esti-":[36],"mators":[37],"methodology":[38],"was":[39,120],"applied,":[40],"which":[41,58],"makes":[42],"resulting":[44],"algo-":[45],"rithm":[46],"independent":[47],"pattern":[50,56],"shape.":[51],"In":[52],"addition,":[53],"elements":[54],"sets":[57],"have":[59,156],"insignificant":[60],"negative":[62],"influence":[63],"on":[64,80,139],"correctness":[66],"are":[69],"eliminated.":[70],"concept":[72,159],"for":[73,125],"realiz-":[74],"ing":[75],"procedure":[77,97],"based":[79],"sensitivity":[82],"method,":[83],"used":[84],"in":[85,115],"domain":[87],"artificial":[89],"neural":[90],"networks.":[91],"As":[92],"a":[93,147],"result":[94],"number":[99],"correct":[101],"classifications":[102],"and":[103,141,162],"-":[104,107],"above":[105],"all":[106],"calculation":[108],"speed":[109],"increased":[110],"significantly.":[111],"A":[112],"further":[113],"growth":[114],"quality":[116],"classifi-":[118],"cation":[119],"achieved":[121],"with":[122,150],"an":[123],"algorithm":[124],"correction":[127],"classifier":[129],"parameter":[130],"values.":[131],"results":[133],"numerical":[135],"verification,":[136],"carried":[137],"out":[138],"pseudorandom":[140],"benchmark":[142],"as":[144,146],"well":[145],"comparative":[148],"analysis":[149],"other":[151],"methods":[152],"similar":[154],"conditioning,":[155],"validated":[157],"its":[163],"positive":[164],"features.":[165]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":5}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}
