{"id":"https://openalex.org/W2912276539","doi":"https://doi.org/10.1016/s1088-467x(99)00002-5","title":"Linear tree","display_name":"Linear tree","publication_year":1999,"publication_date":"1999-05-01","ids":{"openalex":"https://openalex.org/W2912276539","doi":"https://doi.org/10.1016/s1088-467x(99)00002-5","mag":"2912276539"},"language":"it","primary_location":{"id":"doi:10.1016/s1088-467x(99)00002-5","is_oa":false,"landing_page_url":"https://doi.org/10.1016/s1088-467x(99)00002-5","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","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/A5114376321","display_name":"Jo\u00e3o Gama","orcid":"https://orcid.org/0000-0003-3357-1195"},"institutions":[{"id":"https://openalex.org/I182534213","display_name":"Universidade do Porto","ror":"https://ror.org/043pwc612","country_code":"PT","type":"education","lineage":["https://openalex.org/I182534213"]}],"countries":["PT"],"is_corresponding":true,"raw_author_name":"J Gama","raw_affiliation_strings":["LIACC-FEP, University of Porto, Rua Campo Alegre 823, 4150 Porto, Portugal"],"affiliations":[{"raw_affiliation_string":"LIACC-FEP, University of Porto, Rua Campo Alegre 823, 4150 Porto, Portugal","institution_ids":["https://openalex.org/I182534213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5114376321"],"corresponding_institution_ids":["https://openalex.org/I182534213"],"apc_list":null,"apc_paid":null,"fwci":6.6269,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.96756159,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"3","issue":"1","first_page":"1","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9976000189781189,"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"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9976000189781189,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9970999956130981,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9959999918937683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/oblique-case","display_name":"Oblique case","score":0.6864576935768127},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.6014737486839294},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5358695983886719},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5229478478431702},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5144917964935303},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5079846978187561},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4790695607662201},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4589030146598816},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4472709596157074},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.41178637742996216},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3556337356567383},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34766125679016113},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3471181392669678},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.0912930965423584}],"concepts":[{"id":"https://openalex.org/C160697094","wikidata":"https://www.wikidata.org/wiki/Q1233197","display_name":"Oblique case","level":2,"score":0.6864576935768127},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6014737486839294},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5358695983886719},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5229478478431702},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5144917964935303},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5079846978187561},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4790695607662201},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4589030146598816},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4472709596157074},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.41178637742996216},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3556337356567383},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34766125679016113},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3471181392669678},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0912930965423584},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/s1088-467x(99)00002-5","is_oa":false,"landing_page_url":"https://doi.org/10.1016/s1088-467x(99)00002-5","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W18301285","https://openalex.org/W177590838","https://openalex.org/W193228784","https://openalex.org/W1515620500","https://openalex.org/W1516193414","https://openalex.org/W1864487875","https://openalex.org/W1967610656","https://openalex.org/W2006235059","https://openalex.org/W2025653905","https://openalex.org/W2029520384","https://openalex.org/W2104817411","https://openalex.org/W2106596127","https://openalex.org/W2117812871","https://openalex.org/W2149110629","https://openalex.org/W2159080219","https://openalex.org/W2167485767","https://openalex.org/W2982720039","https://openalex.org/W3085162807"],"related_works":["https://openalex.org/W1470425429","https://openalex.org/W4318350883","https://openalex.org/W4328134586","https://openalex.org/W4205478082","https://openalex.org/W3185179407","https://openalex.org/W4281385048","https://openalex.org/W4361795583","https://openalex.org/W4313001487","https://openalex.org/W4308191010","https://openalex.org/W3127425528"],"abstract_inverted_index":{"In":[0],"this":[1,73],"paper":[2],"we":[3,187],"present":[4],"system":[5,167,192],"Ltree":[6,11,53,109],"for":[7,124],"propositional":[8],"supervised":[9],"learning.":[10],"is":[12,34,88,110,132],"able":[13],"to":[14,22,104,150],"define":[15],"decision":[16,38,51,172],"surfaces":[17],"both":[18],"orthogonal":[19],"and":[20,164,176,182,199],"oblique":[21,101],"the":[23,27,30,68,76,92,105,115,140,145,148,151],"axes":[24],"defined":[25],"by":[26,44,59,79],"attributes":[28,63,99],"of":[29,46,61,67],"input":[31,107],"space.":[32,108],"This":[33,84],"done":[35],"combining":[36],"a":[37,41,55,80,111,120],"tree":[39,113,173],"with":[40,102,168],"linear":[42,81],"discriminant":[43,82],"means":[45],"constructive":[47],"induction.":[48],"At":[49],"each":[50,125],"node":[52,74],"defines":[54],"new":[56,62,85,98],"instance":[57,86],"space":[58,87],"insertion":[60],"that":[64,70,117,190],"are":[65,100],"projections":[66],"examples":[69],"fall":[71],"at":[72,134,202],"over":[75],"hyper-planes":[77],"given":[78],"function.":[83],"propagated":[89],"down":[90],"through":[91],"tree.":[93],"Tests":[94],"based":[95],"on":[96,144,159],"those":[97],"respect":[103],"original":[106],"probabilistic":[112],"in":[114,195],"sense":[116],"it":[118],"outputs":[119],"class":[121,129,142],"probability":[122,130],"distribution":[123,131],"query":[126],"example.":[127],"The":[128],"computed":[133],"learning":[135,200],"time,":[136],"taking":[137],"into":[138],"account":[139],"different":[141],"distributions":[143],"path":[146],"from":[147],"root":[149],"actual":[152],"node.":[153],"We":[154],"have":[155,188],"carried":[156],"out":[157],"experiments":[158],"twenty":[160],"one":[161],"benchmark":[162],"datasets":[163,186],"compared":[165],"our":[166,191],"other":[169],"well":[170],"known":[171],"systems":[174],"(orthogonal":[175],"oblique)":[177],"like":[178],"C4.5,":[179],"OC1,":[180],"LMDT,":[181],"CART.":[183],"On":[184],"these":[185],"observed":[189],"has":[193],"advantages":[194],"what":[196],"concerns":[197],"accuracy":[198],"times":[201],"statistically":[203],"significant":[204],"confidence":[205],"levels.":[206]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-02-21T00:00:00"}
