{"id":"https://openalex.org/W2072940401","doi":"https://doi.org/10.1109/coginf.2011.6016141","title":"Rule induction methods with hierachical sampling","display_name":"Rule induction methods with hierachical sampling","publication_year":2011,"publication_date":"2011-08-01","ids":{"openalex":"https://openalex.org/W2072940401","doi":"https://doi.org/10.1109/coginf.2011.6016141","mag":"2072940401"},"language":"en","primary_location":{"id":"doi:10.1109/coginf.2011.6016141","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginf.2011.6016141","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE 10th International Conference on Cognitive Informatics and Cognitive Computing (ICCI-CC'11)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5006566635","display_name":"Shusaku Tsumoto","orcid":"https://orcid.org/0000-0001-6651-976X"},"institutions":[{"id":"https://openalex.org/I169016828","display_name":"Shimane University","ror":"https://ror.org/01jaaym28","country_code":"JP","type":"education","lineage":["https://openalex.org/I169016828"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shusaku Tsumoto","raw_affiliation_strings":["Department of Medical Informatics, Faculty of Medicine, Shimane University, Izumo, Japan","Department of Medical Informatics, Faculty of Medicine, Shimane University, Izumo 693-8501, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Medical Informatics, Faculty of Medicine, Shimane University, Izumo, Japan","institution_ids":["https://openalex.org/I169016828"]},{"raw_affiliation_string":"Department of Medical Informatics, Faculty of Medicine, Shimane University, Izumo 693-8501, Japan","institution_ids":["https://openalex.org/I169016828"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5006566635"],"corresponding_institution_ids":["https://openalex.org/I169016828"],"apc_list":null,"apc_paid":null,"fwci":0.739,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.82685658,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"36","issue":null,"first_page":"193","last_page":"202"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9955999851226807,"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":0.9955999851226807,"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/T10320","display_name":"Neural Networks and Applications","score":0.9901999831199646,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9837999939918518,"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/estimator","display_name":"Estimator","score":0.7086009979248047},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5977656245231628},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5639293789863586},{"id":"https://openalex.org/keywords/rule-induction","display_name":"Rule induction","score":0.4831068515777588},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36422199010849},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35646286606788635},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3048769533634186},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.27978622913360596}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7086009979248047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5977656245231628},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5639293789863586},{"id":"https://openalex.org/C2776780472","wikidata":"https://www.wikidata.org/wiki/Q7378945","display_name":"Rule induction","level":2,"score":0.4831068515777588},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36422199010849},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35646286606788635},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3048769533634186},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27978622913360596},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/coginf.2011.6016141","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginf.2011.6016141","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE 10th International Conference on Cognitive Informatics and Cognitive Computing (ICCI-CC'11)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1514477737","https://openalex.org/W1570286060","https://openalex.org/W1575869149","https://openalex.org/W1594031697","https://openalex.org/W1995945562","https://openalex.org/W2069057356","https://openalex.org/W2098356146","https://openalex.org/W2125055259","https://openalex.org/W2129476886","https://openalex.org/W2136000097","https://openalex.org/W3111627855","https://openalex.org/W4230173782","https://openalex.org/W4234760406","https://openalex.org/W6634111069"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W4287880334","https://openalex.org/W4366700029","https://openalex.org/W4285230481","https://openalex.org/W4385769873","https://openalex.org/W4281634296","https://openalex.org/W4319161863","https://openalex.org/W2371687270","https://openalex.org/W4311888330"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,20],"method":[4,12,45,55],"for":[5,8],"hiearchical":[6],"sampling":[7],"rule":[9],"induction.":[10],"The":[11,50],"generates":[13],"training":[14],"samples":[15,18],"and":[16,24],"test":[17],"in":[19,39],"two-level":[21],"hierarchical":[22],"way,":[23],"compared":[25],"the":[26],"results":[27,51],"between":[28],"these":[29],"two":[30],"levels,":[31],"which":[32],"corresponding":[33],"to":[34,46],"second-order":[35],"approximation":[36],"of":[37],"estimators":[38],"Edgeworth":[40],"expansion.":[41],"We":[42],"applied":[43],"this":[44,54],"three":[47],"medical":[48],"datasets.":[49],"show":[52],"that":[53],"gives":[56],"better":[57],"performance":[58],"than":[59],"conventional":[60],"methods.":[61]},"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}