{"id":"https://openalex.org/W2164338948","doi":"https://doi.org/10.1109/icassp.2004.1327179","title":"Cross-weighted Fisher discriminant analysis for visualization of DNA microarray data","display_name":"Cross-weighted Fisher discriminant analysis for visualization of DNA microarray data","publication_year":2004,"publication_date":"2004-09-28","ids":{"openalex":"https://openalex.org/W2164338948","doi":"https://doi.org/10.1109/icassp.2004.1327179","mag":"2164338948"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2004.1327179","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2004.1327179","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100689719","display_name":"Xinying Zhang","orcid":"https://orcid.org/0000-0002-3416-4623"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinying Zhang","raw_affiliation_strings":["Princeton University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University, USA","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022226374","display_name":"Chad L. Myers","orcid":"https://orcid.org/0000-0002-1026-5972"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"C.L. Myers","raw_affiliation_strings":["Princeton University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University, USA","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072714962","display_name":"Sun\u2010Yuan Kung","orcid":"https://orcid.org/0000-0002-7314-0720"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S.Y. Kung","raw_affiliation_strings":["Princeton University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University, USA","institution_ids":["https://openalex.org/I20089843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20089843"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.19632949,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":null,"first_page":"V","last_page":"589"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9997000098228455,"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":0.9997000098228455,"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/T10057","display_name":"Face and Expression Recognition","score":0.9894999861717224,"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/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9883000254631042,"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":0.7323628664016724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6214587688446045},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6040812134742737},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5806929469108582},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5681455731391907},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.544503390789032},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4939029812812805},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4814800024032593},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.4809783697128296},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.4777078628540039},{"id":"https://openalex.org/keywords/kernel-fisher-discriminant-analysis","display_name":"Kernel Fisher discriminant analysis","score":0.46607303619384766},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.45247048139572144},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4519557058811188},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4424433410167694},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3909916579723358},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19621816277503967},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.08595439791679382}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7323628664016724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6214587688446045},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6040812134742737},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5806929469108582},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5681455731391907},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.544503390789032},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4939029812812805},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4814800024032593},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.4809783697128296},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.4777078628540039},{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.46607303619384766},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.45247048139572144},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4519557058811188},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4424433410167694},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3909916579723358},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19621816277503967},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.08595439791679382}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icassp.2004.1327179","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2004.1327179","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.129.4753","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.129.4753","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.princeton.edu/~kung/ele571/zhang.pdf","raw_type":"text"},{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/37989","is_oa":false,"landing_page_url":"http://hdl.handle.net/10397/37989","pdf_url":null,"source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1770825568","https://openalex.org/W1923333134","https://openalex.org/W1943383135","https://openalex.org/W1964724001","https://openalex.org/W1970127273","https://openalex.org/W1978427245","https://openalex.org/W2018843280","https://openalex.org/W2053186076","https://openalex.org/W2054658115","https://openalex.org/W2109363337","https://openalex.org/W2119668204","https://openalex.org/W2121895507","https://openalex.org/W2124776405","https://openalex.org/W2132549764","https://openalex.org/W2135187880","https://openalex.org/W2137611320","https://openalex.org/W2159793693","https://openalex.org/W2166698530","https://openalex.org/W2797746357","https://openalex.org/W6645096507"],"related_works":["https://openalex.org/W2114217318","https://openalex.org/W1986248657","https://openalex.org/W2756314412","https://openalex.org/W2395040056","https://openalex.org/W3162910294","https://openalex.org/W2196560602","https://openalex.org/W1974303229","https://openalex.org/W2962997812","https://openalex.org/W783379390","https://openalex.org/W1692134900"],"abstract_inverted_index":{"Fisher":[0,95,149],"discriminant":[1],"analysis":[2],"(DA)":[3],"has":[4,41],"recently":[5],"shown":[6],"promise":[7],"in":[8],"dimensionality":[9,158],"reduction":[10],"of":[11,119,141],"high":[12],"dimensional":[13,102],"DNA":[14,47,128],"data.":[15],"However,":[16],"the":[17,31],"1D":[18,81],"projection":[19],"provided":[20],"by":[21,55],"this":[22,114],"method":[23],"is":[24,77,97,108,151],"an":[25],"optimal":[26,137],"Bayesian":[27],"classifier":[28],"only":[29],"when":[30,100],"intraclass":[32,134],"data":[33,49,71,162],"patterns":[34],"are":[35,50,164],"purely":[36],"Gaussian":[37,57],"distributed.":[38],"Unfortunately,":[39],"it":[40],"been":[42],"well":[43],"recognized":[44],"that":[45],"most":[46],"expression":[48],"much":[51],"more":[52],"realistically":[53],"represented":[54],"a":[56,70,75,80,147],"mixture":[58],"model":[59],"(GMM),":[60],"which":[61],"allows":[62],"for":[63,126],"multiple":[64],"cluster":[65,135],"centroids":[66],"per":[67],"class.":[68],"When":[69],"set":[72],"from":[73],"such":[74],"GMM":[76],"projected":[78],"onto":[79],"subspace,":[82],"its":[83,154],"inherent":[84],"multi-modal":[85],"nature":[86],"may":[87],"be":[88],"partially":[89],"or":[90,106],"completely":[91],"obscured.":[92],"Consequently,":[93],"traditional":[94],"DA":[96,150],"quite":[98],"inadequate":[99],"higher":[101],"visualization":[103],"(e.g.":[104],"2D":[105],"3D)":[107],"necessary.":[109],"The":[110],"proposed":[111,152],"technique":[112],"addresses":[113],"problem":[115],"and":[116,122,139,153,159],"makes":[117],"use":[118],"combined":[120],"supervised":[121],"unsupervised":[123],"learning":[124],"techniques":[125],"several":[127],"microarray":[129],"signal":[130],"processing":[131],"functions,":[132],"including":[133],"discovery,":[136],"projection,":[138],"identification/selection":[140],"responsible":[142],"gene":[143],"groups.":[144],"In":[145],"particular,":[146],"cross-weighted":[148],"abilities":[155],"to":[156,160],"reduce":[157],"visualize":[161],"sets":[163],"evaluated.":[165]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}