{"id":"https://openalex.org/W2411469083","doi":"https://doi.org/10.32614/rj-2015-032","title":"treeClust: An R Package for Tree-Based Clustering Dissimilarities","display_name":"treeClust: An R Package for Tree-Based Clustering Dissimilarities","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2411469083","doi":"https://doi.org/10.32614/rj-2015-032","mag":"2411469083"},"language":"en","primary_location":{"id":"doi:10.32614/rj-2015-032","is_oa":true,"landing_page_url":"https://doi.org/10.32614/rj-2015-032","pdf_url":"https://journal.r-project.org/archive/2015/RJ-2015-032/RJ-2015-032.pdf","source":{"id":"https://openalex.org/S2489169438","display_name":"The R Journal","issn_l":"2073-4859","issn":["2073-4859"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The R Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://journal.r-project.org/archive/2015/RJ-2015-032/RJ-2015-032.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004571505","display_name":"\u00c9milie Samuel","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Samuel,E. Buttrey","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5097753499","display_name":"R. Whitaker Lyn","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lyn,R. Whitaker","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5004571505"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.3185,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.93637887,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"7","issue":"2","first_page":"227","last_page":"227"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9962000250816345,"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":0.9962000250816345,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9889000058174133,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9503999948501587,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8237553834915161},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.663907527923584},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5924135446548462},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5624677538871765},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5474057197570801},{"id":"https://openalex.org/keywords/r-package","display_name":"R package","score":0.5377882122993469},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5218745470046997},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.514700710773468},{"id":"https://openalex.org/keywords/multidimensional-scaling","display_name":"Multidimensional scaling","score":0.47524118423461914},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.45032042264938354},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.43963623046875},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38446879386901855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3630148768424988},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35268545150756836},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20731881260871887},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07106345891952515}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8237553834915161},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.663907527923584},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5924135446548462},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5624677538871765},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5474057197570801},{"id":"https://openalex.org/C2984074130","wikidata":"https://www.wikidata.org/wiki/Q73539779","display_name":"R package","level":2,"score":0.5377882122993469},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5218745470046997},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.514700710773468},{"id":"https://openalex.org/C91682802","wikidata":"https://www.wikidata.org/wiki/Q620538","display_name":"Multidimensional scaling","level":2,"score":0.47524118423461914},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.45032042264938354},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.43963623046875},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38446879386901855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3630148768424988},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35268545150756836},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20731881260871887},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07106345891952515},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.32614/rj-2015-032","is_oa":true,"landing_page_url":"https://doi.org/10.32614/rj-2015-032","pdf_url":"https://journal.r-project.org/archive/2015/RJ-2015-032/RJ-2015-032.pdf","source":{"id":"https://openalex.org/S2489169438","display_name":"The R Journal","issn_l":"2073-4859","issn":["2073-4859"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The R Journal","raw_type":"journal-article"},{"id":"pmh:oai:calhoun.nps.edu:10945/48179","is_oa":false,"landing_page_url":"http://hdl.handle.net/10945/48179","pdf_url":null,"source":{"id":"https://openalex.org/S4306400952","display_name":"Calhoun: The Naval Postgraduate School Institutional Archive (Naval Postgraduate School)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I35364215","host_organization_name":"Naval Postgraduate School","host_organization_lineage":["https://openalex.org/I35364215"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:digitalcommons.unl.edu:r-journal-1487","is_oa":false,"landing_page_url":"https://digitalcommons.unl.edu/r-journal/551","pdf_url":null,"source":{"id":"https://openalex.org/S4306513441","display_name":"Insecta mundi","issn_l":"0749-6737","issn":["0749-6737","1942-1354","1942-1362"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310316217","host_organization_name":"Center for Systematic Entomology","host_organization_lineage":["https://openalex.org/P4310316217"],"host_organization_lineage_names":["Center for Systematic Entomology"],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"The R Journal","raw_type":"text"}],"best_oa_location":{"id":"doi:10.32614/rj-2015-032","is_oa":true,"landing_page_url":"https://doi.org/10.32614/rj-2015-032","pdf_url":"https://journal.r-project.org/archive/2015/RJ-2015-032/RJ-2015-032.pdf","source":{"id":"https://openalex.org/S2489169438","display_name":"The R Journal","issn_l":"2073-4859","issn":["2073-4859"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The R Journal","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2411469083.pdf","grobid_xml":"https://content.openalex.org/works/W2411469083.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1594031697","https://openalex.org/W1990643970","https://openalex.org/W1992014701","https://openalex.org/W2021833436","https://openalex.org/W2056884786","https://openalex.org/W2073308541","https://openalex.org/W2089482174","https://openalex.org/W2105909953","https://openalex.org/W2330820318","https://openalex.org/W2346142925","https://openalex.org/W2911964244","https://openalex.org/W3085162807","https://openalex.org/W3120740533","https://openalex.org/W4233815609","https://openalex.org/W4234536190","https://openalex.org/W4399570248","https://openalex.org/W4399576177","https://openalex.org/W6843735874"],"related_works":["https://openalex.org/W4200285273","https://openalex.org/W2374778813","https://openalex.org/W1582127415","https://openalex.org/W2012281976","https://openalex.org/W4238212629","https://openalex.org/W4245539973","https://openalex.org/W2494148009","https://openalex.org/W2314854132","https://openalex.org/W4245095669","https://openalex.org/W4285288111"],"abstract_inverted_index":{"This":[0,43],"paper":[1],"describes":[2],"treeClust,":[3],"an":[4],"R":[5],"package":[6,99],"that":[7,49],"produces":[8,47],"dissimilarities":[9,14,48],"useful":[10,131],"for":[11],"clustering.":[12],"These":[13],"arise":[15],"from":[16,55],"a":[17,35,67,88,103,116,130],"set":[18,76,106,119],"of":[19,45,69,77,127],"classification":[20],"or":[21],"regression":[22],"trees,":[23],"one":[24],"with":[25],"each":[26],"variable":[27,57],"in":[28,32,80,133],"the":[29,36,75,81,83,95,112,125],"data":[30,105,118,135],"acting":[31],"turn":[33],"as":[34,41],"response,":[37],"and":[38,59],"all":[39],"others":[40],"predictors.":[42],"use":[44],"trees":[46],"are":[50],"insensitive":[51],"to":[52,61,71,111],"scaling,":[53],"benefit":[54],"automatic":[56],"selection,":[58],"appear":[60],"perform":[62],"well.":[63],"The":[64,98],"software":[65],"allows":[66],"number":[68],"options":[70],"be":[72,121],"set,":[73],"affecting":[74],"objects":[78],"returned":[79],"call;":[82],"user":[84],"can":[85,100,120],"also":[86,101],"specify":[87],"clustering":[89,96],"algorithm":[90],"and,":[91],"optionally,":[92],"return":[93],"only":[94],"vector.":[97],"generate":[102],"numeric":[104,117],"whose":[107],"inter-point":[108,128],"distances":[109],"relate":[110],"treeClust":[113],"ones;":[114],"such":[115],"much":[122],"smaller":[123],"than":[124],"vector":[126],"dissimilarities,":[129],"feature":[132],"big":[134],"sets.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
