{"id":"https://openalex.org/W2055019958","doi":"https://doi.org/10.1145/1015330.1015372","title":"Incremental learning of linear model trees","display_name":"Incremental learning of linear model trees","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W2055019958","doi":"https://doi.org/10.1145/1015330.1015372","mag":"2055019958"},"language":"en","primary_location":{"id":"doi:10.1145/1015330.1015372","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1015330.1015372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Twenty-first international conference on Machine learning  - ICML '04","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/A5012605616","display_name":"Duncan Potts","orcid":null},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Duncan Potts","raw_affiliation_strings":["Univ. of New South wales, Australia#TAB#"],"affiliations":[{"raw_affiliation_string":"Univ. of New South wales, Australia#TAB#","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5012605616"],"corresponding_institution_ids":["https://openalex.org/I31746571"],"apc_list":null,"apc_paid":null,"fwci":2.4236,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.91537282,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"84","last_page":"84"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9983999729156494,"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":0.9983999729156494,"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":0.996999979019165,"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":0.992900013923645,"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/pruning","display_name":"Pruning","score":0.7624746561050415},{"id":"https://openalex.org/keywords/incremental-decision-tree","display_name":"Incremental decision tree","score":0.7105137705802917},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6844282150268555},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.6583102345466614},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5782844424247742},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.513678252696991},{"id":"https://openalex.org/keywords/id3-algorithm","display_name":"ID3 algorithm","score":0.5124364495277405},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5076786279678345},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4910135567188263},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4816083610057831},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4757130742073059},{"id":"https://openalex.org/keywords/decision-tree-model","display_name":"Decision tree model","score":0.45292794704437256},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.43621790409088135},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.43182191252708435},{"id":"https://openalex.org/keywords/decision-tree-learning","display_name":"Decision tree learning","score":0.3837220370769501},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34167152643203735},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2843495011329651}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7624746561050415},{"id":"https://openalex.org/C10229987","wikidata":"https://www.wikidata.org/wiki/Q17083028","display_name":"Incremental decision tree","level":4,"score":0.7105137705802917},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6844282150268555},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6583102345466614},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5782844424247742},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.513678252696991},{"id":"https://openalex.org/C183931066","wikidata":"https://www.wikidata.org/wiki/Q1653378","display_name":"ID3 algorithm","level":5,"score":0.5124364495277405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5076786279678345},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4910135567188263},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4816083610057831},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4757130742073059},{"id":"https://openalex.org/C56289965","wikidata":"https://www.wikidata.org/wiki/Q5249246","display_name":"Decision tree model","level":3,"score":0.45292794704437256},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.43621790409088135},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.43182191252708435},{"id":"https://openalex.org/C5481197","wikidata":"https://www.wikidata.org/wiki/Q16766476","display_name":"Decision tree learning","level":3,"score":0.3837220370769501},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34167152643203735},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2843495011329651},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1015330.1015372","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1015330.1015372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Twenty-first international conference on Machine learning  - ICML '04","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.1.7699","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.7699","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.aicml.cs.ualberta.ca/banff04/icml/pages/papers/143.ps","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.72.6557","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.72.6557","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://kingman.cs.ualberta.ca/_banff04/icml/pages/papers/143.ps","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W13686424","https://openalex.org/W60322342","https://openalex.org/W148291325","https://openalex.org/W156197890","https://openalex.org/W167515793","https://openalex.org/W182248535","https://openalex.org/W1481566577","https://openalex.org/W1487127700","https://openalex.org/W1492221128","https://openalex.org/W1497915382","https://openalex.org/W1503006878","https://openalex.org/W1503303035","https://openalex.org/W1509296513","https://openalex.org/W1551642208","https://openalex.org/W1552830313","https://openalex.org/W1556347601","https://openalex.org/W1576962511","https://openalex.org/W1594031697","https://openalex.org/W1598333443","https://openalex.org/W1602363634","https://openalex.org/W1636631071","https://openalex.org/W1689445748","https://openalex.org/W1965324089","https://openalex.org/W1966195676","https://openalex.org/W1971845780","https://openalex.org/W1984536024","https://openalex.org/W1997255626","https://openalex.org/W2028628732","https://openalex.org/W2039695762","https://openalex.org/W2064053273","https://openalex.org/W2066442872","https://openalex.org/W2086364952","https://openalex.org/W2107170260","https://openalex.org/W2125055259","https://openalex.org/W2133632100","https://openalex.org/W2167804690","https://openalex.org/W2170396035","https://openalex.org/W2271358270","https://openalex.org/W2477400917","https://openalex.org/W2610419677","https://openalex.org/W2912391306","https://openalex.org/W3085162807"],"related_works":["https://openalex.org/W2120748120","https://openalex.org/W2087668131","https://openalex.org/W1982169401","https://openalex.org/W2363542475","https://openalex.org/W4243803609","https://openalex.org/W2352124552","https://openalex.org/W2364142430","https://openalex.org/W2357812423","https://openalex.org/W2591672004","https://openalex.org/W2361585350"],"abstract_inverted_index":{"A":[0],"linear":[1,10],"model":[2,12,17,45,95],"tree":[3,7,18,79],"is":[4,37,67,90],"a":[5,9,93,105],"decision":[6],"with":[8,57,70],"functional":[11],"in":[13,84],"each":[14],"leaf.":[15],"Previous":[16],"induction":[19],"algorithms":[20],"have":[21],"operated":[22],"on":[23,91],"the":[24,58,75,78,88,97,101,118,124,131],"entire":[25],"training":[26],"set,":[27],"however":[28],"there":[29],"are":[30,121],"many":[31],"situations":[32],"when":[33],"an":[34,52],"incremental":[35,63,71,114],"learner":[36,125],"advantageous.":[38],"In":[39,116],"this":[40],"paper":[41],"we":[42],"demonstrate":[43],"that":[44,54,100],"trees":[46],"can":[47,103],"be":[48],"induced":[49,119],"incrementally":[50],"using":[51],"algorithm":[53,102],"scales":[55],"linearly":[56],"number":[59],"of":[60,77,96],"examples.":[61],"An":[62],"node":[64],"splitting":[65],"rule":[66],"presented,":[68],"together":[69],"methods":[72],"for":[73],"stopping":[74],"growth":[76],"and":[80,123],"pruning.":[81],"Empirical":[82],"testing":[83],"three":[85],"domains,":[86],"where":[87],"emphasis":[89],"learning":[92],"dynamic":[94],"environment,":[98],"shows":[99],"learn":[104],"more":[106],"accurate":[107],"approximation":[108],"from":[109],"fewer":[110],"examples":[111],"than":[112],"other":[113],"methods.":[115],"addition":[117],"models":[120],"smaller,":[122],"requires":[126],"less":[127],"prior":[128],"knowledge":[129],"about":[130],"domain.":[132],"1.":[133]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":3}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}
