{"id":"https://openalex.org/W165601992","doi":null,"title":"Building manageable rough set classifiers.","display_name":"Building manageable rough set classifiers.","publication_year":1998,"publication_date":"1998-01-01","ids":{"openalex":"https://openalex.org/W165601992","mag":"165601992","pmid":"https://pubmed.ncbi.nlm.nih.gov/9929278","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/2232320"},"language":"en","primary_location":{"id":"pmh:oai:pubmedcentral.nih.gov:2232320","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2232320","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proc AMIA Symp","raw_type":"Text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2232320","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004184219","display_name":"Aleksander \u00d8hrn","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I204778367","display_name":"Norwegian University of Science and Technology","ror":"https://ror.org/05xg72x27","country_code":"NO","type":"education","lineage":["https://openalex.org/I204778367"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"A Ohrn","raw_affiliation_strings":["Dept. of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway. aleks@idi.ntnu.no"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway. aleks@idi.ntnu.no","institution_ids":["https://openalex.org/I204778367"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084415954","display_name":"Lucila Ohno-machado A","orcid":"https://orcid.org/0000-0002-8005-7327","observed_orcids":["https://orcid.org/0000-0002-8005-7327"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"L Ohno-Machado","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5053709165","display_name":"Todd Rowland","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"T Rowland","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7462,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.88230856,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"543","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.0003000000142492354,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.0,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/rough-set-theory","display_name":"rough set theory","score":0.9629999995231628},{"id":"https://openalex.org/keywords/rule-based-classifiers","display_name":"rule-based classifiers","score":0.953000009059906},{"id":"https://openalex.org/keywords/boolean-reasoning","display_name":"Boolean reasoning","score":0.9829999804496765},{"id":"https://openalex.org/keywords/model-reduction","display_name":"model reduction","score":0.6330000162124634},{"id":"https://openalex.org/keywords/hypothesis-generation","display_name":"hypothesis generation","score":0.48399999737739563},{"id":"https://openalex.org/keywords/knowledge-discovery","display_name":"knowledge discovery","score":0.6520000100135803},{"id":"https://openalex.org/keywords/medical-data-classification","display_name":"medical data classification","score":0.6299999952316284},{"id":"https://openalex.org/keywords/interpretable-models","display_name":"interpretable models","score":0.6159999966621399},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.515999972820282}],"concepts":[{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.8314783573150635},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7053834795951843},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.6720778346061707},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6575802564620972},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.594307541847229},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.5541184544563293},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5169795751571655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.509774386882782},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41408810019493103},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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}],"mesh":[{"descriptor_ui":"D002965","descriptor_name":"Classification","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D003627","descriptor_name":"Data Interpretation, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003661","descriptor_name":"Decision Support Techniques","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":true},{"descriptor_ui":"D017143","descriptor_name":"Fuzzy Logic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"pmh:oai:pubmedcentral.nih.gov:2232320","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2232320","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proc AMIA Symp","raw_type":"Text"},{"id":"pmid:9929278","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/9929278","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. AMIA Symposium","raw_type":"Journal Article"},{"id":"mag:165601992","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/9929278","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"PubMed","raw_type":null}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:2232320","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2232320","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proc AMIA Symp","raw_type":"Text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G7732953174","display_name":"COMPONENT BASED TOOLS FOR CONNECTIONIST CLASSIFICATION","funder_award_id":"R01LM006538","funder_id":"https://openalex.org/F4320337372","funder_display_name":"U.S. National Library of Medicine"},{"id":"https://openalex.org/G9000904321","display_name":"Biomedical Informatics and Data Science Research Training Program (BIRT)","funder_award_id":"T15LM007092","funder_id":"https://openalex.org/F4320337372","funder_display_name":"U.S. National Library of Medicine"}],"funders":[{"id":"https://openalex.org/F4320337372","display_name":"U.S. National Library of Medicine","ror":"https://ror.org/0060t0j89"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W2157825442"],"related_works":["https://openalex.org/W3185121043","https://openalex.org/W2069322654","https://openalex.org/W2105243781","https://openalex.org/W2123248133","https://openalex.org/W1568715940","https://openalex.org/W1606515631","https://openalex.org/W1983955072","https://openalex.org/W75319390","https://openalex.org/W2369231620","https://openalex.org/W1891724360"],"abstract_inverted_index":{"An":[0],"interesting":[1],"aspect":[2],"of":[3,28,110,117,130],"techniques":[4],"for":[5,14],"data":[6],"mining":[7],"and":[8,35,78,85,122,128],"knowledge":[9],"discovery":[10],"is":[11,31,44,120],"their":[12],"potential":[13],"generating":[15],"hypotheses":[16,30],"by":[17],"discovering":[18],"underlying":[19],"relationships":[20],"buried":[21],"in":[22],"the":[23,26,36,51,97,111,115,131],"data.":[24],"However,":[25],"set":[27,76],"possible":[29],"often":[32],"very":[33],"large":[34],"extracted":[37],"models":[38,57,99],"may":[39],"become":[40],"prohibitively":[41],"complex.":[42],"It":[43],"therefore":[45],"typically":[46],"desirable":[47],"to":[48,92,102],"only":[49,107],"consider":[50],"\"strongest\"":[52],"hypotheses,":[53],"so":[54],"that":[55,61,81],"smaller":[56],"can":[58,88],"be":[59,89],"obtained":[60],"also":[62],"retain":[63],"good":[64,104],"classificatory":[65],"capabilities.":[66],"This":[67],"paper":[68],"outlines":[69],"how":[70],"rule-based":[71],"classifiers":[72],"based":[73],"on":[74],"rough":[75],"theory":[77],"Boolean":[79],"reasoning":[80],"are":[82,100],"both":[83],"small":[84],"perform":[86],"well":[87],"developed.":[90],"Applied":[91],"a":[93,108,125],"real-world":[94],"medical":[95],"dataset,":[96],"final":[98],"shown":[101],"exhibit":[103],"performance":[105],"using":[106],"subset":[109],"available":[112],"information.":[113],"Furthermore,":[114],"number":[116],"resulting":[118],"rules":[119],"low":[121],"enables":[123],"practical":[124],"posteriori":[126],"inspection":[127],"interpretation":[129],"models.":[132]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2016-06-24T00:00:00"}