{"id":"https://openalex.org/W2949918273","doi":"https://doi.org/10.1109/iccabs.2018.8542038","title":"So you think you can PLS-DA?","display_name":"So you think you can PLS-DA?","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2949918273","doi":"https://doi.org/10.1109/iccabs.2018.8542038","mag":"2949918273"},"language":"en","primary_location":{"id":"doi:10.1109/iccabs.2018.8542038","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccabs.2018.8542038","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 8th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)","raw_type":"proceedings-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/A5022556011","display_name":"Daniel Ruiz-Perez","orcid":"https://orcid.org/0000-0002-5622-560X"},"institutions":[{"id":"https://openalex.org/I19700959","display_name":"Florida International University","ror":"https://ror.org/02gz6gg07","country_code":"US","type":"education","lineage":["https://openalex.org/I19700959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Ruiz-Perez","raw_affiliation_strings":["Bioinformatics Research Group (BioRG), Florida International University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bioinformatics Research Group (BioRG), Florida International University","institution_ids":["https://openalex.org/I19700959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102786133","display_name":"Haibin Guan","orcid":"https://orcid.org/0000-0001-8096-443X"},"institutions":[{"id":"https://openalex.org/I19700959","display_name":"Florida International University","ror":"https://ror.org/02gz6gg07","country_code":"US","type":"education","lineage":["https://openalex.org/I19700959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haibin Guan","raw_affiliation_strings":["Bioinformatics Research Group (BioRG), Florida International University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bioinformatics Research Group (BioRG), Florida International University","institution_ids":["https://openalex.org/I19700959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016248967","display_name":"Purnima Madhivanan","orcid":"https://orcid.org/0000-0001-7818-3394"},"institutions":[{"id":"https://openalex.org/I19700959","display_name":"Florida International University","ror":"https://ror.org/02gz6gg07","country_code":"US","type":"education","lineage":["https://openalex.org/I19700959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Purnima Madhivanan","raw_affiliation_strings":["Department of Epidemiology, Florida International University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Epidemiology, Florida International University","institution_ids":["https://openalex.org/I19700959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037360822","display_name":"Kalai Mathee","orcid":"https://orcid.org/0000-0003-4569-5419"},"institutions":[{"id":"https://openalex.org/I19700959","display_name":"Florida International University","ror":"https://ror.org/02gz6gg07","country_code":"US","type":"education","lineage":["https://openalex.org/I19700959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kalai Mathee","raw_affiliation_strings":["Herbert Wertheim College of Medicine, Florida International University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Herbert Wertheim College of Medicine, Florida International University","institution_ids":["https://openalex.org/I19700959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068890173","display_name":"Giri Narasimhan","orcid":"https://orcid.org/0000-0003-0535-4871"},"institutions":[{"id":"https://openalex.org/I19700959","display_name":"Florida International University","ror":"https://ror.org/02gz6gg07","country_code":"US","type":"education","lineage":["https://openalex.org/I19700959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Giri Narasimhan","raw_affiliation_strings":["Bioinformatics Research Group (BioRG), Florida International University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bioinformatics Research Group (BioRG), Florida International University","institution_ids":["https://openalex.org/I19700959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6184,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.80758185,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9955000281333923,"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":0.9955000281333923,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9843000173568726,"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/T12388","display_name":"Identification and Quantification in Food","score":0.9753000140190125,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7144896984100342},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7126725912094116},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6667991876602173},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6348433494567871},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5991260409355164},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.590981125831604},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5836998224258423},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.5076900720596313},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.495386004447937},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3810564875602722},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3320573568344116}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7144896984100342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7126725912094116},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6667991876602173},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6348433494567871},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5991260409355164},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.590981125831604},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5836998224258423},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.5076900720596313},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.495386004447937},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3810564875602722},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3320573568344116}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccabs.2018.8542038","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccabs.2018.8542038","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 8th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306078","display_name":"U.S. Department of Defense","ror":"https://ror.org/0447fe631"},{"id":"https://openalex.org/F4320309993","display_name":"Florida International University","ror":"https://ror.org/02gz6gg07"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2052589448","https://openalex.org/W2765337000","https://openalex.org/W3104072235","https://openalex.org/W2391447249","https://openalex.org/W2312955079","https://openalex.org/W2350996391","https://openalex.org/W2066119650","https://openalex.org/W2059615944","https://openalex.org/W4224057882","https://openalex.org/W2037752115"],"abstract_inverted_index":{"Partial":[0],"Least-Squares":[1],"Discriminant":[2],"Analysis":[3,58],"(PLS-DA)":[4],"is":[5,12,94,187],"a":[6,17,34,84,155,161,193,207,214],"popular":[7],"machine":[8],"learning":[9],"tool":[10,78],"that":[11,62,167],"gaining":[13],"increasing":[14],"attention":[15],"as":[16,83,154,158,160],"useful":[18],"feature":[19,85,114,156,252],"selector":[20,157],"and":[21,30,41,122,128,144,262],"classifier.":[22,162],"In":[23,87,163],"an":[24,237],"effort":[25],"to":[26,45,117],"understand":[27],"its":[28,43,46,102],"strengths":[29,261],"weaknesses,":[31],"we":[32,165,235],"performed":[33],"series":[35],"of":[36,73,97,142,210,231,264],"experiments":[37,104],"with":[38,147,268],"synthetic":[39],"data":[40,145,239],"compared":[42],"performance":[44,216],"close":[47],"relative":[48],"from":[49,106,241],"which":[50,93,148],"it":[51,90,186],"was":[52,254],"initially":[53],"invented,":[54],"namely":[55],"Principal":[56],"Component":[57],"(PCA).":[59],"We":[60],"demonstrate":[61],"even":[63,200,217],"though":[64],"PCA":[65],"ignores":[66],"the":[67,70,74,98,109,113,140,183,190,197,219,229,232,247,251,257,260],"information":[68],"regarding":[69],"class":[71,99],"labels":[72,100],"samples,":[75],"this":[76],"unsupervised":[77],"can":[79,150],"be":[80,151],"remarkably":[81],"effective":[82,152,188],"selector.":[86],"some":[88],"cases,":[89],"outperforms":[91],"PLS-DA,":[92],"made":[95],"aware":[96],"in":[101,112,223,228,266],"input.Our":[103],"range":[105],"looking":[107],"at":[108],"signal-to-noise":[110],"ratio":[111],"selection":[115,253],"task,":[116],"considering":[118],"many":[119],"practical":[120],"distributions":[121],"models":[123,146],"encountered":[124],"when":[125,168,189,201,218],"analyzing":[126],"bioinformatics":[127],"clinical":[129],"data.":[130,184],"Other":[131],"methods":[132],"were":[133],"also":[134],"evaluated.Our":[135],"work":[136],"sheds":[137],"light":[138],"on":[139,196],"kind":[141],"relationships":[143],"PLS-DA":[149,177,212,265],"both":[153],"well":[159],"particular,":[164],"claim":[166],"classes":[169,191,220],"are":[170,204,221],"determined":[171],"by":[172],"linear":[173],"or":[174],"non-linear":[175],"relationships,":[176],"provides":[178],"almost":[179],"no":[180],"insight":[181],"into":[182],"But":[185],"have":[192],"clustered":[194],"distribution":[195],"signal":[198,233],"features,":[199],"these":[202],"features":[203],"hidden":[205],"among":[206],"large":[208],"number":[209],"noise.":[211],"retains":[213],"strong":[215],"contained":[222],"n-orthotopes":[224],"(i.e.,":[225],"rectangular":[226],"boxes":[227],"subspace":[230],"features).Finally,":[234],"analyzed":[236],"interesting":[238],"set":[240],"396":[242],"vaginal":[243],"microbiome":[244],"samples":[245],"where":[246],"ground":[248],"truth":[249],"for":[250],"available.":[255],"Again,":[256],"results":[258],"highlighted":[259],"weaknesses":[263],"comparison":[267],"PCA.":[269]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
