{"id":"https://openalex.org/W2785372418","doi":"https://doi.org/10.1021/acs.jcim.7b00649","title":"Discussion on Regression Methods Based on Ensemble Learning and Applicability Domains of Linear Submodels","display_name":"Discussion on Regression Methods Based on Ensemble Learning and Applicability Domains of Linear Submodels","publication_year":2018,"publication_date":"2018-02-09","ids":{"openalex":"https://openalex.org/W2785372418","doi":"https://doi.org/10.1021/acs.jcim.7b00649","mag":"2785372418","pmid":"https://pubmed.ncbi.nlm.nih.gov/29425038"},"language":"en","primary_location":{"id":"doi:10.1021/acs.jcim.7b00649","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.7b00649","pdf_url":null,"source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5082283686","display_name":"Hiromasa Kaneko","orcid":"https://orcid.org/0000-0001-8367-6476"},"institutions":[{"id":"https://openalex.org/I16656306","display_name":"Meiji University","ror":"https://ror.org/02rqvrp93","country_code":"JP","type":"education","lineage":["https://openalex.org/I16656306"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hiromasa Kaneko","raw_affiliation_strings":["Department of Applied Chemistry, School\rof Science and Technology, Meiji University, 1-1-1 Higashi-Mita, Tama-ku, Kawasaki, Kanagawa 214-8571, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Applied Chemistry, School\rof Science and Technology, Meiji University, 1-1-1 Higashi-Mita, Tama-ku, Kawasaki, Kanagawa 214-8571, Japan","institution_ids":["https://openalex.org/I16656306"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5082283686"],"corresponding_institution_ids":["https://openalex.org/I16656306"],"apc_list":null,"apc_paid":null,"fwci":0.317,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.51725582,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"58","issue":"2","first_page":"480","last_page":"489"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9864000082015991,"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/ensemble-learning","display_name":"Ensemble learning","score":0.662431001663208},{"id":"https://openalex.org/keywords/cheminformatics","display_name":"Cheminformatics","score":0.5804834961891174},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5521081686019897},{"id":"https://openalex.org/keywords/chemometrics","display_name":"Chemometrics","score":0.5430291891098022},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.5326328873634338},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5273326635360718},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.523443877696991},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.5008111000061035},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48480096459388733},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4694520831108093},{"id":"https://openalex.org/keywords/regression-diagnostic","display_name":"Regression diagnostic","score":0.46164339780807495},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.45233580470085144},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.44513827562332153},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43928101658821106},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3423112630844116},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24169155955314636},{"id":"https://openalex.org/keywords/bayesian-multivariate-linear-regression","display_name":"Bayesian multivariate linear regression","score":0.21388089656829834},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.07551172375679016}],"concepts":[{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.662431001663208},{"id":"https://openalex.org/C68762167","wikidata":"https://www.wikidata.org/wiki/Q910164","display_name":"Cheminformatics","level":2,"score":0.5804834961891174},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5521081686019897},{"id":"https://openalex.org/C151304367","wikidata":"https://www.wikidata.org/wiki/Q910067","display_name":"Chemometrics","level":2,"score":0.5430291891098022},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.5326328873634338},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5273326635360718},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.523443877696991},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5008111000061035},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48480096459388733},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4694520831108093},{"id":"https://openalex.org/C57381214","wikidata":"https://www.wikidata.org/wiki/Q55631393","display_name":"Regression diagnostic","level":4,"score":0.46164339780807495},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.45233580470085144},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.44513827562332153},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43928101658821106},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3423112630844116},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24169155955314636},{"id":"https://openalex.org/C64946054","wikidata":"https://www.wikidata.org/wiki/Q4874476","display_name":"Bayesian multivariate linear regression","level":3,"score":0.21388089656829834},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.07551172375679016},{"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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C147597530","wikidata":"https://www.wikidata.org/wiki/Q369472","display_name":"Computational chemistry","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008958","descriptor_name":"Models, Molecular","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008958","descriptor_name":"Models, Molecular","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008958","descriptor_name":"Models, Molecular","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012044","descriptor_name":"Regression Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012044","descriptor_name":"Regression Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012044","descriptor_name":"Regression Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012995","descriptor_name":"Solubility","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012995","descriptor_name":"Solubility","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012995","descriptor_name":"Solubility","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014867","descriptor_name":"Water","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D014867","descriptor_name":"Water","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D014867","descriptor_name":"Water","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D021281","descriptor_name":"Quantitative Structure-Activity Relationship","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D021281","descriptor_name":"Quantitative Structure-Activity Relationship","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D021281","descriptor_name":"Quantitative Structure-Activity Relationship","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1021/acs.jcim.7b00649","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.7b00649","pdf_url":null,"source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},{"id":"pmid:29425038","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29425038","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of chemical information and modeling","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1601795611","https://openalex.org/W1605688901","https://openalex.org/W1739877739","https://openalex.org/W1786301341","https://openalex.org/W1965395794","https://openalex.org/W1975875826","https://openalex.org/W1977405994","https://openalex.org/W1988195734","https://openalex.org/W1997175832","https://openalex.org/W2007302339","https://openalex.org/W2010524461","https://openalex.org/W2010933199","https://openalex.org/W2025836881","https://openalex.org/W2026939352","https://openalex.org/W2029799473","https://openalex.org/W2035288789","https://openalex.org/W2039774147","https://openalex.org/W2041392558","https://openalex.org/W2042278642","https://openalex.org/W2050150264","https://openalex.org/W2052329328","https://openalex.org/W2057965448","https://openalex.org/W2073503722","https://openalex.org/W2074359970","https://openalex.org/W2077736710","https://openalex.org/W2079699273","https://openalex.org/W2089468765","https://openalex.org/W2089578131","https://openalex.org/W2092977448","https://openalex.org/W2097793132","https://openalex.org/W2128245586","https://openalex.org/W2176009755","https://openalex.org/W2217436801","https://openalex.org/W2397554732","https://openalex.org/W2420937411","https://openalex.org/W2616127448","https://openalex.org/W2757711895","https://openalex.org/W2898867502","https://openalex.org/W2919115771","https://openalex.org/W4241421973","https://openalex.org/W4250955420"],"related_works":["https://openalex.org/W4200131390","https://openalex.org/W2794896638","https://openalex.org/W2891633941","https://openalex.org/W4390905871","https://openalex.org/W3202800081","https://openalex.org/W3101614107","https://openalex.org/W1909207154","https://openalex.org/W3036530763","https://openalex.org/W1514365828","https://openalex.org/W4390971112"],"abstract_inverted_index":{"To":[0],"develop":[1],"a":[2,46,64,94,101],"new":[3],"ensemble":[4,24],"learning":[5,25],"method":[6],"and":[7,15,62,83,100,116],"construct":[8],"highly":[9],"predictive":[10],"regression":[11,121],"models":[12,122],"in":[13],"chemoinformatics":[14],"chemometrics,":[16],"applicability":[17],"domains":[18],"(ADs)":[19],"are":[20,57],"introduced":[21],"into":[22],"the":[23,40,50,54,70,73,78,84,111,117],"process":[26],"of":[27,32,66,72,120],"prediction.":[28],"When":[29],"estimating":[30],"values":[31],"an":[33],"objective":[34],"variable":[35],"using":[36],"subregression":[37],"models,":[38],"only":[39],"submodels":[41,61],"with":[42,126],"ADs":[43,112],"that":[44,110],"cover":[45],"query":[47],"sample,":[48],"i.e.,":[49],"sample":[51],"is":[52,87,108,123],"inside":[53],"model's":[55],"AD,":[56,80],"used.":[58],"By":[59,92],"constructing":[60],"changing":[63],"list":[65],"selected":[67],"explanatory":[68],"variables,":[69],"union":[71],"submodels'":[74],"ADs,":[75],"which":[76],"defines":[77],"overall":[79],"becomes":[81],"large,":[82],"prediction":[85],"performance":[86,119],"enhanced":[88],"for":[89],"diverse":[90],"compounds.":[91],"analyzing":[93],"quantitative":[95,102],"structure-activity":[96],"relationship":[97,104],"data":[98,105],"set":[99],"structure-property":[103],"set,":[106],"it":[107],"confirmed":[109],"can":[113],"be":[114],"enlarged":[115],"estimation":[118],"improved":[124],"compared":[125],"traditional":[127],"methods.":[128]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
