{"id":"https://openalex.org/W2059282376","doi":"https://doi.org/10.1007/3-540-63223-9_113","title":"Regression-based classification methods and their comparison with decision tree algorithms","display_name":"Regression-based classification methods and their comparison with decision tree algorithms","publication_year":1997,"publication_date":"1997-01-01","ids":{"openalex":"https://openalex.org/W2059282376","doi":"https://doi.org/10.1007/3-540-63223-9_113","mag":"2059282376"},"language":"en","primary_location":{"id":"doi:10.1007/3-540-63223-9_113","is_oa":true,"landing_page_url":"https://doi.org/10.1007/3-540-63223-9_113","pdf_url":"https://link.springer.com/content/pdf/10.1007/3-540-63223-9_113.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"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":"book series"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/3-540-63223-9_113.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031421685","display_name":"Mikhail Kiselev","orcid":"https://orcid.org/0000-0001-7403-6418"},"institutions":[{"id":"https://openalex.org/I4210096645","display_name":"Megaputer Intelligence (United States)","ror":"https://ror.org/00d3dc551","country_code":"US","type":"company","lineage":["https://openalex.org/I4210096645"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mikhail V. Kiselev","raw_affiliation_strings":["Megaputer Intelligence Ltd., 38 B.Tatarskaya, 113184, Moscow, Russia","Megaputer Intelligence Ltd"],"affiliations":[{"raw_affiliation_string":"Megaputer Intelligence Ltd., 38 B.Tatarskaya, 113184, Moscow, Russia","institution_ids":[]},{"raw_affiliation_string":"Megaputer Intelligence Ltd","institution_ids":["https://openalex.org/I4210096645"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066068563","display_name":"Sergei M. Ananyan","orcid":null},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]},{"id":"https://openalex.org/I267592682","display_name":"Williams (United States)","ror":"https://ror.org/007zhvp17","country_code":"US","type":"company","lineage":["https://openalex.org/I267592682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sergei M. Ananyan","raw_affiliation_strings":["Department of Physics, College of William and Mary, 23187, Williamsburg, VA, USA","college of william and mary"],"affiliations":[{"raw_affiliation_string":"Department of Physics, College of William and Mary, 23187, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]},{"raw_affiliation_string":"college of william and mary","institution_ids":["https://openalex.org/I16285277"]}]},{"author_position":"last","author":{"id":null,"display_name":"Sergei B. Arseniev","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096645","display_name":"Megaputer Intelligence (United States)","ror":"https://ror.org/00d3dc551","country_code":"US","type":"company","lineage":["https://openalex.org/I4210096645"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sergei B. Arseniev","raw_affiliation_strings":["Megaputer Intelligence Ltd., 38 B.Tatarskaya, 113184, Moscow, Russia","Megaputer Intelligence Ltd"],"affiliations":[{"raw_affiliation_string":"Megaputer Intelligence Ltd., 38 B.Tatarskaya, 113184, Moscow, Russia","institution_ids":[]},{"raw_affiliation_string":"Megaputer Intelligence Ltd","institution_ids":["https://openalex.org/I4210096645"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5031421685"],"corresponding_institution_ids":["https://openalex.org/I4210096645"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":3.8526,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.93490305,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"134","last_page":"144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9997000098228455,"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9715999960899353,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13141","display_name":"Statistical Methods and Applications","score":0.9685999751091003,"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/decision-tree","display_name":"Decision tree","score":0.7501784563064575},{"id":"https://openalex.org/keywords/decision-tree-learning","display_name":"Decision tree learning","score":0.5964475870132446},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4949573874473572},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.49140632152557373},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4847823977470398},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4817900061607361},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47636839747428894},{"id":"https://openalex.org/keywords/id3-algorithm","display_name":"ID3 algorithm","score":0.4679872989654541},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4577462077140808},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4471644163131714},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4421384632587433},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.4409295320510864},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.41207632422447205},{"id":"https://openalex.org/keywords/incremental-decision-tree","display_name":"Incremental decision tree","score":0.3804129660129547},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38012146949768066},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20234832167625427}],"concepts":[{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.7501784563064575},{"id":"https://openalex.org/C5481197","wikidata":"https://www.wikidata.org/wiki/Q16766476","display_name":"Decision tree learning","level":3,"score":0.5964475870132446},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4949573874473572},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.49140632152557373},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4847823977470398},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4817900061607361},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47636839747428894},{"id":"https://openalex.org/C183931066","wikidata":"https://www.wikidata.org/wiki/Q1653378","display_name":"ID3 algorithm","level":5,"score":0.4679872989654541},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4577462077140808},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4471644163131714},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4421384632587433},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4409295320510864},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.41207632422447205},{"id":"https://openalex.org/C10229987","wikidata":"https://www.wikidata.org/wiki/Q17083028","display_name":"Incremental decision tree","level":4,"score":0.3804129660129547},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38012146949768066},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20234832167625427},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/3-540-63223-9_113","is_oa":true,"landing_page_url":"https://doi.org/10.1007/3-540-63223-9_113","pdf_url":"https://link.springer.com/content/pdf/10.1007/3-540-63223-9_113.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"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":"book series"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/3-540-63223-9_113","is_oa":true,"landing_page_url":"https://doi.org/10.1007/3-540-63223-9_113","pdf_url":"https://link.springer.com/content/pdf/10.1007/3-540-63223-9_113.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"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":"book series"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.800000011920929,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2059282376.pdf","grobid_xml":"https://content.openalex.org/works/W2059282376.grobid-xml"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W1558092570","https://openalex.org/W2048997388","https://openalex.org/W2125055259","https://openalex.org/W2153476503","https://openalex.org/W2330820318","https://openalex.org/W3085162807","https://openalex.org/W4206495155","https://openalex.org/W4285719527","https://openalex.org/W6600051819"],"related_works":["https://openalex.org/W2030894524","https://openalex.org/W1648970942","https://openalex.org/W2188355725","https://openalex.org/W2143508752","https://openalex.org/W1982169401","https://openalex.org/W4387869645","https://openalex.org/W2592385415","https://openalex.org/W3197772267","https://openalex.org/W2167102385","https://openalex.org/W2622249843"],"abstract_inverted_index":{"Classification":[0],"learning":[1],"can":[2,45,73],"be":[3,46,74],"considered":[4,47],"as":[5,48],"a":[6,53],"regression":[7,33,43],"problem":[8,21,90],"with":[9],"dependent":[10],"variable":[11],"consisting":[12],"of":[13,22,70],"0s":[14],"and":[15,92],"1s.":[16],"Reducing":[17],"classification":[18],"to":[19,30,58,86],"the":[20,37,62,68,88,105],"finding":[23],"numerical":[24],"dependencies":[25],"we":[26],"gain":[27],"an":[28],"opportunity":[29],"utilize":[31],"powerful":[32],"methods":[34],"implemented":[35],"in":[36],"PolyAnalyst":[38],"data":[39],"mining":[40],"system.":[41],"Resulting":[42],"functions":[44],"fuzzy":[49],"membership":[50],"indicators":[51],"for":[52,76],"recognized":[54],"class.":[55],"In":[56],"order":[57],"obtain":[59],"classifying":[60],"rules,":[61],"optimum":[63],"threshold":[64],"values":[65],"which":[66],"minimize":[67],"number":[69],"misclassified":[71],"cases":[72],"found":[75],"these":[77],"functions.":[78],"We":[79],"show":[80],"that":[81,95],"this":[82],"approach":[83],"allows":[84],"one":[85],"solve":[87],"over-fit":[89],"satisfactorily":[91],"provides":[93],"results":[94,102],"are":[96],"at":[97],"least":[98],"not":[99],"worse":[100],"than":[101],"obtained":[103],"by":[104],"most":[106],"popular":[107],"decision":[108],"tree":[109],"algorithms.":[110]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
