{"id":"https://openalex.org/W4220928232","doi":"https://doi.org/10.1080/03610918.2022.2047201","title":"Different thresholding methods on Nearest Shrunken Centroid algorithm","display_name":"Different thresholding methods on Nearest Shrunken Centroid algorithm","publication_year":2022,"publication_date":"2022-03-07","ids":{"openalex":"https://openalex.org/W4220928232","doi":"https://doi.org/10.1080/03610918.2022.2047201"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2022.2047201","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2047201","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2501.00632","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059521666","display_name":"Mohammad Sahtout","orcid":"https://orcid.org/0000-0003-0217-1826"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammad Omar Sahtout","raw_affiliation_strings":["Department of Statistics, University of California, Davis, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of California, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100354447","display_name":"Haiyan Wang","orcid":"https://orcid.org/0000-0002-2523-0465"},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Haiyan Wang","raw_affiliation_strings":["Department of Statistics, Kansas State University, Manhattan, KS, USA"],"raw_orcid":"https://orcid.org/0000-0002-2523-0465","affiliations":[{"raw_affiliation_string":"Department of Statistics, Kansas State University, Manhattan, KS, USA","institution_ids":["https://openalex.org/I189590672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005322552","display_name":"Santosh Ghimire","orcid":"https://orcid.org/0000-0003-4488-2271"},"institutions":[{"id":"https://openalex.org/I155028946","display_name":"Tribhuvan University","ror":"https://ror.org/02rg1r889","country_code":"NP","type":"education","lineage":["https://openalex.org/I155028946"]},{"id":"https://openalex.org/I4405263138","display_name":"Pulchowk Campus","ror":"https://ror.org/034bmrt60","country_code":"NP","type":"education","lineage":["https://openalex.org/I155028946","https://openalex.org/I4210129773","https://openalex.org/I4405263138"]}],"countries":["NP"],"is_corresponding":false,"raw_author_name":"Santosh Ghimire","raw_affiliation_strings":["Department of Applied Sciences and Chemical Engineering, Pulchowk Campus, Tribhuvan University, Kirtipur, Nepal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Sciences and Chemical Engineering, Pulchowk Campus, Tribhuvan University, Kirtipur, Nepal","institution_ids":["https://openalex.org/I155028946","https://openalex.org/I4405263138"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100354447"],"corresponding_institution_ids":["https://openalex.org/I189590672"],"apc_list":null,"apc_paid":null,"fwci":0.0784,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.35824407,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"53","issue":"3","first_page":"1444","last_page":"1460"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9905999898910522,"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"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.9529045224189758},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.7187356948852539},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6004775762557983},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5754849910736084},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.539103627204895},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3925137519836426},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3201017379760742},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12896347045898438}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.9529045224189758},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.7187356948852539},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6004775762557983},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5754849910736084},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.539103627204895},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3925137519836426},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3201017379760742},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12896347045898438}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/03610918.2022.2047201","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2047201","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:arXiv.org:2501.00632","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.00632","pdf_url":"https://arxiv.org/pdf/2501.00632","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2501.00632","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.00632","pdf_url":"https://arxiv.org/pdf/2501.00632","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4238960123","display_name":null,"funder_award_id":"246077","funder_id":"https://openalex.org/F4320306164","funder_display_name":"Simons Foundation"}],"funders":[{"id":"https://openalex.org/F4320306164","display_name":"Simons Foundation","ror":"https://ror.org/01cmst727"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4220928232.pdf"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1513088205","https://openalex.org/W1727290854","https://openalex.org/W1965528589","https://openalex.org/W1988790447","https://openalex.org/W1991108537","https://openalex.org/W2000771269","https://openalex.org/W2017784810","https://openalex.org/W2049701820","https://openalex.org/W2059856562","https://openalex.org/W2094660994","https://openalex.org/W2097255042","https://openalex.org/W2097413644","https://openalex.org/W2102247676","https://openalex.org/W2109363337","https://openalex.org/W2117526678","https://openalex.org/W2137476312","https://openalex.org/W2138218344","https://openalex.org/W2138550913","https://openalex.org/W2147246240","https://openalex.org/W2153635508","https://openalex.org/W2157531738","https://openalex.org/W2158940042","https://openalex.org/W2171528238","https://openalex.org/W2295598076","https://openalex.org/W2911964244","https://openalex.org/W3037530356","https://openalex.org/W4212883601","https://openalex.org/W4246697467","https://openalex.org/W4293584363","https://openalex.org/W4294541781"],"related_works":["https://openalex.org/W2381926679","https://openalex.org/W1542224353","https://openalex.org/W1661087619","https://openalex.org/W2116854923","https://openalex.org/W2750730210","https://openalex.org/W2007009951","https://openalex.org/W2236974868","https://openalex.org/W4312766348","https://openalex.org/W4233939244","https://openalex.org/W2082644203"],"abstract_inverted_index":{"This":[0],"article":[1],"considers":[2],"the":[3,10,20,44,87,106,138,151],"impact":[4],"of":[5,23,46,71,172],"different":[6],"thresholding":[7,32,112,126],"methods":[8],"to":[9,33,53,76,93,123,137],"Nearest":[11],"Shrunken":[12],"Centroid":[13],"algorithm,":[14],"which":[15,90],"is":[16,86,91],"popularly":[17],"referred":[18],"as":[19],"Prediction":[21],"Analysis":[22],"Microarrays":[24],"(PAM)":[25],"for":[26],"high-dimensional":[27],"classification.":[28],"PAM":[29,57,107],"uses":[30],"soft":[31,88],"achieve":[34,124],"high":[35,39],"computational":[36],"efficiency":[37],"and":[38,115,118,135,145],"classification":[40],"accuracy":[41],"but":[42,161],"in":[43,98,164],"price":[45],"retaining":[47],"too":[48],"many":[49],"features.":[50,173],"When":[51],"applied":[52],"microarray":[54],"human":[55],"cancers,":[56],"selected":[58],"2611":[59],"features":[60,72],"on":[61,142],"average":[62],"from":[63],"10":[64],"multi-class":[65],"datasets.":[66],"Such":[67],"a":[68,119],"large":[69],"number":[70,171],"make":[73],"it":[74],"difficult":[75],"perform":[77],"follow":[78],"up":[79],"study.":[80],"One":[81],"reason":[82],"behind":[83],"this":[84,102],"problem":[85],"thresholding,":[89,117],"known":[92],"produce":[94],"biased":[95],"parameter":[96,127],"estimate":[97],"regression":[99],"analysis.":[100],"In":[101,149],"article,":[103],"we":[104],"extend":[105],"algorithm":[108,122],"with":[109,168],"two":[110],"other":[111],"methods,":[113],"hard":[114],"order":[116],"deep":[120],"search":[121],"better":[125,156],"estimate.":[128],"The":[129],"modified":[130],"algorithms":[131],"are":[132],"extensively":[133],"tested":[134],"compared":[136],"original":[139],"one":[140],"based":[141],"real":[143],"data":[144],"Monte":[146],"Carlo":[147],"studies.":[148],"general,":[150],"modification":[152],"not":[153],"only":[154],"gave":[155],"cancer":[157],"status":[158],"prediction":[159],"accuracy,":[160],"also":[162],"resulted":[163],"more":[165],"parsimonious":[166],"models":[167],"significantly":[169],"smaller":[170]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-25T17:18:41.151588","created_date":"2025-10-10T00:00:00"}