{"id":"https://openalex.org/W2015529673","doi":"https://doi.org/10.1007/s10618-012-0287-5","title":"Using coarse information for real valued prediction","display_name":"Using coarse information for real valued prediction","publication_year":2012,"publication_date":"2012-08-13","ids":{"openalex":"https://openalex.org/W2015529673","doi":"https://doi.org/10.1007/s10618-012-0287-5","mag":"2015529673"},"language":"en","primary_location":{"id":"doi:10.1007/s10618-012-0287-5","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10618-012-0287-5","pdf_url":null,"source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-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/A5077627355","display_name":"Amit Dhurandhar","orcid":"https://orcid.org/0000-0002-3579-1450"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Amit Dhurandhar","raw_affiliation_strings":["IBM T.J. Watson, Yorktown Heights, NY, USA","IBM T. J. Watson, Yorktown Heights, USA"],"affiliations":[{"raw_affiliation_string":"IBM T.J. Watson, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I1341412227"]},{"raw_affiliation_string":"IBM T. J. Watson, Yorktown Heights, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5077627355"],"corresponding_institution_ids":["https://openalex.org/I1341412227"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":null,"fwci":0.4762,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.72687112,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"27","issue":"2","first_page":"167","last_page":"192"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12114","display_name":"Sensory Analysis and Statistical Methods","score":0.9686999917030334,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12114","display_name":"Sensory Analysis and Statistical Methods","score":0.9686999917030334,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9552000164985657,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9527000188827515,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.721264123916626},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.6171737909317017},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5966548919677734},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5774069428443909},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5602735280990601},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.5552079677581787},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5182273387908936},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5013432502746582},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4228230118751526},{"id":"https://openalex.org/keywords/mean-squared-prediction-error","display_name":"Mean squared prediction error","score":0.4121996760368347},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38598811626434326},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35830000042915344},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3553754389286041},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1870533525943756}],"concepts":[{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.721264123916626},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.6171737909317017},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5966548919677734},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5774069428443909},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5602735280990601},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.5552079677581787},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5182273387908936},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5013432502746582},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4228230118751526},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.4121996760368347},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38598811626434326},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35830000042915344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3553754389286041},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1870533525943756},{"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},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10618-012-0287-5","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10618-012-0287-5","pdf_url":null,"source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5699999928474426,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1480376833","https://openalex.org/W1540144755","https://openalex.org/W1581592866","https://openalex.org/W1587682423","https://openalex.org/W1601741105","https://openalex.org/W1990757206","https://openalex.org/W2016381774","https://openalex.org/W2098421151","https://openalex.org/W2111799408","https://openalex.org/W2118418963","https://openalex.org/W2118584553","https://openalex.org/W2142234361","https://openalex.org/W2152966212","https://openalex.org/W2167144043","https://openalex.org/W2167277498","https://openalex.org/W2337193626","https://openalex.org/W2497171922","https://openalex.org/W2766742239","https://openalex.org/W2787894218"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W4256502920","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2999756192","https://openalex.org/W2059697060","https://openalex.org/W4382701072","https://openalex.org/W4387967938"],"abstract_inverted_index":null,"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}