{"id":"https://openalex.org/W2947894340","doi":"https://doi.org/10.1080/03610918.2019.1620274","title":"Improving <i>K</i>-means method via shrinkage estimation and LVQ algorithm","display_name":"Improving <i>K</i>-means method via shrinkage estimation and LVQ algorithm","publication_year":2019,"publication_date":"2019-05-30","ids":{"openalex":"https://openalex.org/W2947894340","doi":"https://doi.org/10.1080/03610918.2019.1620274","mag":"2947894340"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1620274","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1620274","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-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/A5012901072","display_name":"Zhouping Li","orcid":"https://orcid.org/0000-0003-0979-4110"},"institutions":[{"id":"https://openalex.org/I4210152533","display_name":"Lanzhou University of Finance and Economics","ror":"https://ror.org/04v7yv031","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152533"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhouping Li","raw_affiliation_strings":["School of Mathematics and Statistics, Lanzhou University, Lanzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Lanzhou University, Lanzhou, China","institution_ids":["https://openalex.org/I4210152533"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100460860","display_name":"Hui Wang","orcid":"https://orcid.org/0000-0002-9412-3516"},"institutions":[{"id":"https://openalex.org/I4210152533","display_name":"Lanzhou University of Finance and Economics","ror":"https://ror.org/04v7yv031","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152533"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Wang","raw_affiliation_strings":["School of Mathematics and Statistics, Lanzhou University, Lanzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Lanzhou University, Lanzhou, China","institution_ids":["https://openalex.org/I4210152533"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5012901072"],"corresponding_institution_ids":["https://openalex.org/I4210152533"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05024706,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"50","issue":"11","first_page":"3166","last_page":"3181"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9958000183105469,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9958000183105469,"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/T10057","display_name":"Face and Expression Recognition","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/shrinkage","display_name":"Shrinkage","score":0.9013213515281677},{"id":"https://openalex.org/keywords/learning-vector-quantization","display_name":"Learning vector quantization","score":0.6693793535232544},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5400458574295044},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4684334695339203},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3916706442832947},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3582848906517029},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.21561852097511292},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.048889338970184326}],"concepts":[{"id":"https://openalex.org/C180145272","wikidata":"https://www.wikidata.org/wiki/Q7504144","display_name":"Shrinkage","level":2,"score":0.9013213515281677},{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.6693793535232544},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5400458574295044},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4684334695339203},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3916706442832947},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3582848906517029},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.21561852097511292},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.048889338970184326}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1080/03610918.2019.1620274","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1620274","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"},{"id":"pmh:oai:ir.lzu.edu.cn/:262010/294867","is_oa":false,"landing_page_url":"http://ir.lzu.edu.cn/handle/262010/294867","pdf_url":null,"source":{"id":"https://openalex.org/S4406923049","display_name":"Lanzhou University Institutional Repository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:ir.lzu.edu.cn/:262010/372784","is_oa":false,"landing_page_url":"http://ir.lzu.edu.cn/handle/262010/372784","pdf_url":null,"source":{"id":"https://openalex.org/S4406923049","display_name":"Lanzhou University Institutional Repository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:ir.lzu.edu.cn/:262010/468728","is_oa":false,"landing_page_url":"http://ir.lzu.edu.cn/handle/262010/468728","pdf_url":null,"source":{"id":"https://openalex.org/S4406923049","display_name":"Lanzhou University Institutional Repository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal article (JA)"},{"id":"pmh:oai:ir.lzu.edu.cn/:262010/276886","is_oa":false,"landing_page_url":"http://ir.lzu.edu.cn/handle/262010/276886","pdf_url":null,"source":{"id":"https://openalex.org/S4406923049","display_name":"Lanzhou University Institutional Repository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:ir.lzu.edu.cn/:262010/285480","is_oa":false,"landing_page_url":"http://ir.lzu.edu.cn/handle/262010/285480","pdf_url":null,"source":{"id":"https://openalex.org/S4406923049","display_name":"Lanzhou University Institutional Repository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5194078000","display_name":null,"funder_award_id":"11571154","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7952563055","display_name":null,"funder_award_id":"lzujbky-2018-110","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327557","display_name":"National Office for Philosophy and Social Sciences","ror":"https://ror.org/04m0ms912"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W87092222","https://openalex.org/W1983349993","https://openalex.org/W1985622505","https://openalex.org/W1992419399","https://openalex.org/W1994241229","https://openalex.org/W2027863679","https://openalex.org/W2028125409","https://openalex.org/W2033403400","https://openalex.org/W2051891923","https://openalex.org/W2103868202","https://openalex.org/W2288950719","https://openalex.org/W2299467264","https://openalex.org/W2319660501","https://openalex.org/W2567289819","https://openalex.org/W2586376538","https://openalex.org/W2623590165","https://openalex.org/W2733722625","https://openalex.org/W2963481827","https://openalex.org/W3105265400","https://openalex.org/W3120740533","https://openalex.org/W4235169531","https://openalex.org/W4244998381","https://openalex.org/W4302561155"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2360214423","https://openalex.org/W2156017042","https://openalex.org/W2391958761","https://openalex.org/W1647056466","https://openalex.org/W2765453142","https://openalex.org/W2137852660","https://openalex.org/W2356780078","https://openalex.org/W2356008845","https://openalex.org/W255134961"],"abstract_inverted_index":{"Clustering":[0],"is":[1,44],"an":[2,17],"important":[3],"task":[4],"in":[5,59],"statistics":[6],"and":[7,31,55,79,91],"many":[8],"other":[9],"scientific":[10],"fields.":[11],"In":[12],"this":[13,41,88],"note,":[14],"we":[15,61],"propose":[16],"improved":[18],"K-means":[19],"clustering":[20,54,64],"approach":[21],"called":[22],"\u2018enhanced":[23],"shrinkage":[24],"K-means\u2019":[25],"based":[26],"on":[27],"the":[28,49,63,67,85],"James-Stein":[29,71],"estimator":[30],"learning":[32],"vector":[33,69],"quantization":[34],"(LVQ)":[35],"algorithm.":[36],"The":[37],"basic":[38],"idea":[39],"of":[40,48,51,87],"new":[42,89],"algorithm":[43],"taking":[45],"into":[46],"account":[47],"strength":[50],"both":[52],"unsupervised":[53],"supervised":[56],"classification":[57],"methods,":[58],"which":[60],"shrink":[62],"centers":[65],"toward":[66],"prototype":[68],"via":[70],"estimator.":[72],"We":[73],"carry":[74],"out":[75],"extensive":[76],"simulation":[77],"studies":[78],"real":[80],"data":[81],"analysis":[82],"to":[83],"evaluate":[84],"performance":[86],"approach,":[90],"obtain":[92],"encouraging":[93],"results.":[94]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-06-07T00:00:00"}