{"id":"https://openalex.org/W7157961008","doi":"https://doi.org/10.48550/arxiv.2604.25304","title":"RCProb: Probabilistic Rule Extraction for Efficient Simplification of Tree Ensembles","display_name":"RCProb: Probabilistic Rule Extraction for Efficient Simplification of Tree Ensembles","publication_year":2026,"publication_date":"2026-04-28","ids":{"openalex":"https://openalex.org/W7157961008","doi":"https://doi.org/10.48550/arxiv.2604.25304"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.25304","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.25304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.25304","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064081309","display_name":"Josue Obregon","orcid":"https://orcid.org/0000-0002-4021-7672"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Obregon, Josue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5064081309"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9286999702453613,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9286999702453613,"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":0.009700000286102295,"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":0.0071000000461936,"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/probabilistic-logic","display_name":"Probabilistic logic","score":0.6287999749183655},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5726000070571899},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5691999793052673},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5658000111579895},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5633999705314636},{"id":"https://openalex.org/keywords/probabilistic-classification","display_name":"Probabilistic classification","score":0.44769999384880066},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.39879998564720154},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.3862999975681305},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.38530001044273376}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6575999855995178},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6287999749183655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6157000064849854},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5881999731063843},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5726000070571899},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5691999793052673},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5658000111579895},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5633999705314636},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4616999924182892},{"id":"https://openalex.org/C189119545","wikidata":"https://www.wikidata.org/wiki/Q5128022","display_name":"Probabilistic classification","level":4,"score":0.44769999384880066},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.39879998564720154},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.3862999975681305},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.38530001044273376},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3564999997615814},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3499999940395355},{"id":"https://openalex.org/C5481197","wikidata":"https://www.wikidata.org/wiki/Q16766476","display_name":"Decision tree learning","level":3,"score":0.3402000069618225},{"id":"https://openalex.org/C10229987","wikidata":"https://www.wikidata.org/wiki/Q17083028","display_name":"Incremental decision tree","level":4,"score":0.33559998869895935},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C56289965","wikidata":"https://www.wikidata.org/wiki/Q5249246","display_name":"Decision tree model","level":3,"score":0.2987000048160553},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C104317236","wikidata":"https://www.wikidata.org/wiki/Q4330126","display_name":"Classification rule","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26010000705718994},{"id":"https://openalex.org/C207024777","wikidata":"https://www.wikidata.org/wiki/Q621673","display_name":"Search tree","level":3,"score":0.2574999928474426},{"id":"https://openalex.org/C63002673","wikidata":"https://www.wikidata.org/wiki/Q2260590","display_name":"Scoring rule","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C84839998","wikidata":"https://www.wikidata.org/wiki/Q5249245","display_name":"Decision rule","level":2,"score":0.2524999976158142},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.25304","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.25304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.25304","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.25304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Tree":[0],"ensembles":[1,67],"are":[2],"widely":[3],"used":[4],"in":[5,25],"industrial":[6],"machine":[7],"learning":[8],"due":[9],"to":[10,37,70,116,139],"their":[11],"strong":[12],"predictive":[13,73,179],"performance":[14,74,180],"and":[15,101,155],"efficient":[16],"training":[17,114],"procedures.":[18],"However,":[19],"as":[20],"the":[21,29,72,76,113,141],"number":[22],"of":[23,54,61,75,136,144],"trees":[24],"an":[26],"ensemble":[27],"grows,":[28],"resulting":[30],"models":[31,52,93],"become":[32],"increasingly":[33],"difficult":[34],"for":[35,89,124],"humans":[36],"interpret.":[38],"To":[39],"address":[40],"this":[41,128],"limitation,":[42],"explainable":[43],"artificial":[44],"intelligence":[45],"(XAI)":[46],"studies":[47],"methods":[48],"that":[49,175],"generate":[50],"interpretable":[51,102],"capable":[53],"explaining":[55],"complex":[56],"predictors.":[57],"One":[58],"approach":[59],"consists":[60],"extracting":[62,90],"decision":[63],"rules":[64],"from":[65,94],"tree":[66,95],"while":[68,181,190],"attempting":[69],"preserve":[71],"original":[77],"model.":[78],"In":[79,127],"previous":[80],"work,":[81],"we":[82,130],"introduced":[83],"RuleCOSI+,":[84,189],"a":[85,133,161],"greedy":[86],"heuristic":[87],"algorithm":[88],"compact":[91,193],"rule-based":[92],"ensembles.":[96],"Although":[97],"RuleCOSI+":[98,137],"produces":[99],"accurate":[100],"rule":[103,118,145,149,194],"sets,":[104],"it":[105],"relies":[106],"on":[107,170,196],"repeated":[108,166],"empirical":[109],"frequency":[110],"counting":[111],"over":[112],"data":[115],"estimate":[117],"confidence,":[119],"which":[120],"becomes":[121],"computationally":[122],"expensive":[123],"large":[125],"datasets.":[126],"paper,":[129],"propose":[131],"RCProb,":[132],"probabilistic":[134],"reformulation":[135],"designed":[138],"reduce":[140],"computational":[142],"cost":[143],"extraction.":[146],"RCProb":[147,176],"estimates":[148],"statistics":[150],"using":[151],"Dirichlet-smoothed":[152],"class":[153],"priors":[154],"Beta-smoothed":[156],"condition":[157],"likelihoods":[158],"combined":[159],"through":[160],"Naive":[162],"Bayes":[163],"formulation,":[164],"avoiding":[165],"dataset":[167],"scans.":[168],"Experiments":[169],"33":[171],"benchmark":[172],"datasets":[173],"show":[174],"maintains":[177],"competitive":[178],"reducing":[182],"runtime":[183],"by":[184],"approximately":[185],"$22\\times$":[186],"compared":[187],"with":[188],"producing":[191],"more":[192],"sets":[195],"average.":[197]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-30T00:00:00"}