{"id":"https://openalex.org/W3096406566","doi":"https://doi.org/10.3390/informatics7040050","title":"Investigation of Combining Logitboost(M5P) under Active Learning Classification Tasks","display_name":"Investigation of Combining Logitboost(M5P) under Active Learning Classification Tasks","publication_year":2020,"publication_date":"2020-11-03","ids":{"openalex":"https://openalex.org/W3096406566","doi":"https://doi.org/10.3390/informatics7040050","mag":"3096406566"},"language":"en","primary_location":{"id":"doi:10.3390/informatics7040050","is_oa":true,"landing_page_url":"https://doi.org/10.3390/informatics7040050","pdf_url":"https://www.mdpi.com/2227-9709/7/4/50/pdf?version=1604404401","source":{"id":"https://openalex.org/S2738238905","display_name":"Informatics","issn_l":"2227-9709","issn":["2227-9709"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2227-9709/7/4/50/pdf?version=1604404401","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069837137","display_name":"Vangjel Kazllarof","orcid":"https://orcid.org/0000-0003-4545-3866"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Vangjel Kazllarof","raw_affiliation_strings":["Department of Mathematics, University of Patras, 26500 Patras, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Patras, 26500 Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073119708","display_name":"Stamatis Karlos","orcid":"https://orcid.org/0000-0002-5307-6186"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Stamatis Karlos","raw_affiliation_strings":["Department of Mathematics, University of Patras, 26500 Patras, Greece"],"raw_orcid":"https://orcid.org/0000-0002-5307-6186","affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Patras, 26500 Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066370772","display_name":"Sotiris Kotsiantis","orcid":"https://orcid.org/0000-0002-2247-3082"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Sotiris Kotsiantis","raw_affiliation_strings":["Department of Mathematics, University of Patras, 26500 Patras, Greece"],"raw_orcid":"https://orcid.org/0000-0002-2247-3082","affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Patras, 26500 Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5069837137"],"corresponding_institution_ids":["https://openalex.org/I174878644"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":0.4077,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.70613851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"7","issue":"4","first_page":"50","last_page":"50"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9995999932289124,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9995999932289124,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9972000122070312,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9933000206947327,"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/machine-learning","display_name":"Machine learning","score":0.8111239671707153},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8009887933731079},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7759589552879333},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5459654331207275},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5445073843002319},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5179371237754822},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5037199854850769},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.478293240070343},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4618681073188782},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.46060875058174133},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.42884087562561035},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12666741013526917},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10904526710510254}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.8111239671707153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8009887933731079},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7759589552879333},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5459654331207275},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5445073843002319},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5179371237754822},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5037199854850769},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.478293240070343},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4618681073188782},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.46060875058174133},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.42884087562561035},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12666741013526917},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10904526710510254},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/informatics7040050","is_oa":true,"landing_page_url":"https://doi.org/10.3390/informatics7040050","pdf_url":"https://www.mdpi.com/2227-9709/7/4/50/pdf?version=1604404401","source":{"id":"https://openalex.org/S2738238905","display_name":"Informatics","issn_l":"2227-9709","issn":["2227-9709"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:83df7eee31324eb98e9ac3c9e90c1a2d","is_oa":true,"landing_page_url":"https://doaj.org/article/83df7eee31324eb98e9ac3c9e90c1a2d","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Informatics, Vol 7, Iss 4, p 50 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2227-9709/7/4/50/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/informatics7040050","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Informatics; Volume 7; Issue 4; Pages: 50","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/informatics7040050","is_oa":true,"landing_page_url":"https://doi.org/10.3390/informatics7040050","pdf_url":"https://www.mdpi.com/2227-9709/7/4/50/pdf?version=1604404401","source":{"id":"https://openalex.org/S2738238905","display_name":"Informatics","issn_l":"2227-9709","issn":["2227-9709"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.550000011920929,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3096406566.pdf","grobid_xml":"https://content.openalex.org/works/W3096406566.grobid-xml"},"referenced_works_count":72,"referenced_works":["https://openalex.org/W5410279","https://openalex.org/W13188192","https://openalex.org/W396371331","https://openalex.org/W1145034317","https://openalex.org/W1547683487","https://openalex.org/W1557418592","https://openalex.org/W1647002864","https://openalex.org/W1981039744","https://openalex.org/W1987552279","https://openalex.org/W2024046085","https://openalex.org/W2024360430","https://openalex.org/W2038969939","https://openalex.org/W2043360138","https://openalex.org/W2044074081","https://openalex.org/W2071049913","https://openalex.org/W2079020577","https://openalex.org/W2081635953","https://openalex.org/W2112076978","https://openalex.org/W2122892819","https://openalex.org/W2133990480","https://openalex.org/W2139432865","https://openalex.org/W2164400088","https://openalex.org/W2168020168","https://openalex.org/W2181558882","https://openalex.org/W2230749025","https://openalex.org/W2275382787","https://openalex.org/W2293353568","https://openalex.org/W2295598076","https://openalex.org/W2342049278","https://openalex.org/W2408920689","https://openalex.org/W2511186734","https://openalex.org/W2523927452","https://openalex.org/W2527200289","https://openalex.org/W2547164840","https://openalex.org/W2581151820","https://openalex.org/W2595314642","https://openalex.org/W2606436201","https://openalex.org/W2727699974","https://openalex.org/W2735449402","https://openalex.org/W2746791238","https://openalex.org/W2755846764","https://openalex.org/W2757280805","https://openalex.org/W2766196489","https://openalex.org/W2769911997","https://openalex.org/W2782546864","https://openalex.org/W2789887073","https://openalex.org/W2794670721","https://openalex.org/W2889353337","https://openalex.org/W2902029421","https://openalex.org/W2945920492","https://openalex.org/W2970199969","https://openalex.org/W2970529432","https://openalex.org/W2972945228","https://openalex.org/W2980536865","https://openalex.org/W2982318248","https://openalex.org/W2982353106","https://openalex.org/W2986737700","https://openalex.org/W2999479658","https://openalex.org/W3001459730","https://openalex.org/W3016230452","https://openalex.org/W3036090607","https://openalex.org/W3039293784","https://openalex.org/W3102476541","https://openalex.org/W3121208640","https://openalex.org/W4298132949","https://openalex.org/W6600233308","https://openalex.org/W6661564606","https://openalex.org/W6676769703","https://openalex.org/W6723941685","https://openalex.org/W6725535599","https://openalex.org/W6745964985","https://openalex.org/W6756573903"],"related_works":["https://openalex.org/W4386295066","https://openalex.org/W4225647658","https://openalex.org/W2073883415","https://openalex.org/W3108206494","https://openalex.org/W2905156999","https://openalex.org/W4229460275","https://openalex.org/W2739726746","https://openalex.org/W4242380336","https://openalex.org/W4366990902","https://openalex.org/W4317732970"],"abstract_inverted_index":{"Active":[0],"learning":[1,45,120,135,218],"is":[2,10,41],"the":[3,18,26,34,58,71,80,87,90,102,163,178,184,188,191,203,235,243,249,261,285,288],"category":[4],"of":[5,21,36,61,89,97,104,165,180,183,190,246,263,271,274,287],"partially":[6],"supervised":[7,227],"algorithms":[8,46,99],"that":[9,202,220,252],"differentiated":[11],"by":[12],"its":[13,125],"strategy":[14],"to":[15,31,42,144,280],"combine":[16],"both":[17,211],"predictive":[19],"ability":[20],"a":[22,94,108,132,157,167],"base":[23,110],"learner":[24,111],"and":[25,68,146,213,299],"human":[27,72],"knowledge":[28],"so":[29],"as":[30,207,240,242],"exploit":[32],"adequately":[33],"existence":[35],"unlabeled":[37],"data.":[38],"Its":[39,230],"ambition":[40],"compose":[43],"powerful":[44],"which":[47,100,140],"otherwise":[48],"would":[49,221],"be":[50,75,222,281],"based":[51,112],"only":[52],"on":[53,113,224],"insufficient":[54],"labelled":[55],"samples.":[56],"Since":[57,187],"latter":[59],"kind":[60],"information":[62],"could":[63,209],"raise":[64],"important":[65],"monetization":[66],"costs":[67],"time":[69],"obstacles,":[70],"contribution":[73],"should":[74],"seriously":[76],"restricted":[77],"compared":[78],"with":[79,107,156],"former.":[81],"For":[82],"this":[83,255],"reason,":[84],"we":[85,176,200],"investigate":[86],"use":[88],"Logitboost":[91,154],"wrapper":[92],"classifier,":[93],"popular":[95],"variant":[96,155],"ensemble":[98],"adopts":[101],"technique":[103,193],"boosting":[105,192],"along":[106],"regression":[109,170],"Model":[114],"trees":[115,277],"into":[116],"3":[117],"different":[118],"active":[119,134,217],"query":[121],"strategies.":[122],"We":[123,149,291],"study":[124],"efficiency":[126],"against":[127],"10":[128],"separate":[129,158],"learners":[130],"under":[131,216],"well-described":[133],"framework":[136],"over":[137,234,260],"91":[138],"datasets":[139],"have":[141],"been":[142],"split":[143],"binary":[145],"multi-class":[147],"problems.":[148,290],"also":[150],"included":[151],"one":[152,181],"typical":[153],"internal":[159],"regressor":[160],"for":[161,284],"discriminating":[162],"benefits":[164],"adopting":[166],"more":[168,282],"accurate":[169,212,244],"tree":[171],"than":[172],"one-node":[173],"trees,":[174],"while":[175,269],"examined":[177,289],"efficacy":[179],"hyperparameter":[182],"proposed":[185,204],"algorithm.":[186],"application":[189],"may":[194],"provide":[195,210],"overall":[196],"less":[197],"biased":[198],"predictions,":[199],"assume":[201],"algorithm,":[205],"named":[206],"Logitboost(M5P),":[208],"robust":[214],"decisions":[215],"scenarios":[219],"beneficial":[223],"real-life":[225],"weakly":[226],"classification":[228,264],"tasks.":[229],"smoother":[231],"weighting":[232],"stage":[233],"misclassified":[236],"cases":[237],"during":[238],"training":[239],"well":[241],"behavior":[245],"M5P":[247,272],"are":[248],"main":[250],"factors":[251],"lead":[253],"towards":[254],"performance.":[256],"Proper":[257],"statistical":[258],"comparisons":[259],"metric":[262],"accuracy":[265],"verify":[266],"our":[267,293,303],"assumptions,":[268],"adoption":[270],"instead":[273],"weak":[275],"decision":[276],"was":[278],"proven":[279],"competitive":[283],"majority":[286],"present":[292],"results":[294,304],"through":[295],"appropriate":[296],"summarization":[297],"approaches":[298],"explanatory":[300],"visualizations,":[301],"commenting":[302],"per":[305],"case.":[306]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
