{"id":"https://openalex.org/W51173251","doi":null,"title":"Identifying Decision Lists with the Discrete Function Learning Algorithm","display_name":"Identifying Decision Lists with the Discrete Function Learning Algorithm","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W51173251","mag":"51173251"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.497.834","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.497.834","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www3.ntu.edu.sg/home/asckkwoh/My Conferences/c2004 Zheng2004AISAT-identifying-v12.pdf","raw_type":"text"},"volume":null,"type":"conference-paper","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/A5053747834","display_name":"Yun Zheng","orcid":"https://orcid.org/0000-0003-4292-9806","observed_orcids":["https://orcid.org/0000-0003-4292-9806"]},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Yun Zheng","raw_affiliation_strings":["Nanyang Technological University"],"raw_orcid":"https://orcid.org/0000-0003-4292-9806","affiliations":[{"raw_affiliation_string":"Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5053747834"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.3861,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.52562289,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.8339999914169312,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.8339999914169312,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.07410000264644623,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.038100000470876694,"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/decision-lists","display_name":"decision lists","score":0.9919999837875366},{"id":"https://openalex.org/keywords/rule-based-classifiers","display_name":"rule-based classifiers","score":0.8539999723434448},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.7720000147819519},{"id":"https://openalex.org/keywords/noise-handling","display_name":"noise handling","score":0.5759999752044678},{"id":"https://openalex.org/keywords/overfitting-avoidance","display_name":"overfitting avoidance","score":0.9089999794960022},{"id":"https://openalex.org/keywords/biological-characteristics","display_name":"biological characteristics","score":0.5289999842643738},{"id":"https://openalex.org/keywords/classification-accuracy","display_name":"classification accuracy","score":0.492000013589859}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.814913272857666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6642789840698242},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5869125127792358},{"id":"https://openalex.org/C95627357","wikidata":"https://www.wikidata.org/wiki/Q7979889","display_name":"Weighted Majority Algorithm","level":5,"score":0.5438873767852783},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5359450578689575},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5281933546066284},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5100215077400208},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42481136322021484},{"id":"https://openalex.org/C17061570","wikidata":"https://www.wikidata.org/wiki/Q7960888","display_name":"Wake-sleep algorithm","level":4,"score":0.17259472608566284},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.16818279027938843},{"id":"https://openalex.org/C117765406","wikidata":"https://www.wikidata.org/wiki/Q5362437","display_name":"Generalization error","level":3,"score":0.07653820514678955},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.497.834","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.497.834","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www3.ntu.edu.sg/home/asckkwoh/My Conferences/c2004 Zheng2004AISAT-identifying-v12.pdf","raw_type":"text"},{"id":"mag:51173251","doi":null,"is_oa":false,"landing_page_url":"https://www3.ntu.edu.sg/home/asckkwoh/My%20Conferences/c2004%20Zheng2004AISAT-identifying-v12.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"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":30,"referenced_works":["https://openalex.org/W94571269","https://openalex.org/W187660804","https://openalex.org/W1483135265","https://openalex.org/W1504694836","https://openalex.org/W1515040589","https://openalex.org/W1531743498","https://openalex.org/W1549485114","https://openalex.org/W1570286060","https://openalex.org/W1570329253","https://openalex.org/W1576962511","https://openalex.org/W1637435380","https://openalex.org/W1670263352","https://openalex.org/W1817561967","https://openalex.org/W1927345150","https://openalex.org/W1980073965","https://openalex.org/W1999138184","https://openalex.org/W2033139852","https://openalex.org/W2084812512","https://openalex.org/W2111746072","https://openalex.org/W2121629952","https://openalex.org/W2125055259","https://openalex.org/W2136000097","https://openalex.org/W2136061550","https://openalex.org/W2149706766","https://openalex.org/W2170335877","https://openalex.org/W2189004000","https://openalex.org/W2428981601","https://openalex.org/W2799061466","https://openalex.org/W2963331194","https://openalex.org/W2982720039"],"related_works":["https://openalex.org/W7096025196","https://openalex.org/W1488104855","https://openalex.org/W2074818257","https://openalex.org/W7099170357","https://openalex.org/W187660804","https://openalex.org/W7100437041","https://openalex.org/W2112284223","https://openalex.org/W2260945667","https://openalex.org/W4229900359","https://openalex.org/W4240181179"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,30,78,106,129],"novel":[6],"method":[7,107,127],"to":[8,40,59,81,110,117,132],"learn":[9],"deci-sion":[10],"lists":[11],"(classifiers":[12],"as":[13],"sets":[14],"of":[15,32,44,53,99],"rules)":[16],"with":[17,85,91,112],"the":[18,37,45,54,61,65,74,92,100,125,133],"Discrete":[19],"Func-tion":[20],"Learning":[21],"(DFL)":[22],"algorithm.":[23,135],"The":[24,69,88,120],"DFL":[25,62,75,93,134],"algorithm":[26,63,76,94],"works":[27],"by":[28],"finding":[29],"subset":[31],"attributes":[33,98],"which":[34],"gives":[35],"all":[36],"needed":[38],"information":[39],"decide":[41],"group":[42],"attribute":[43],"cases.":[46],"We":[47,103],"per-form":[48],"experiments":[49],"on":[50],"some":[51],"datasets":[52,115],"UCI":[55],"machine":[56],"learning":[57],"repository":[58],"validate":[60],"and":[64,116],"proposed":[66],"prediction":[67],"method.":[68],"experimental":[70],"results":[71,122],"show":[72,123],"that":[73,124],"achieves":[77],"competitive":[79],"accuracy":[80],"current":[82],"classification":[83],"methods":[84],"excellent":[86],"efficiency.":[87],"classifiers":[89],"learned":[90],"contain":[95],"biolog-ically":[96],"critical":[97],"corresponding":[101],"datasets.":[102],"further":[104],"introduce":[105],"called":[108],"function":[109,126],"deal":[111],"noises":[113],"in":[114],"avoid":[118],"overfitting.":[119],"experimen-tal":[121],"is":[128],"good":[130],"supple-ment":[131],"1.":[136]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2026-09-26T08:19:03.415552","created_date":"2016-06-24T00:00:00"}