{"id":"https://openalex.org/W1644308042","doi":"https://doi.org/10.1109/ijcnn.2015.7280792","title":"Threshold optimization of pseudo-inverse linear discriminants based on overall accuracies","display_name":"Threshold optimization of pseudo-inverse linear discriminants based on overall accuracies","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W1644308042","doi":"https://doi.org/10.1109/ijcnn.2015.7280792","mag":"1644308042"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2015.7280792","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2015.7280792","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Joint Conference on Neural Networks (IJCNN)","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/A5109056896","display_name":"Tain Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tain Tian","raw_affiliation_strings":["East China University of Science and Technology, Shanghai, Shanghai, CN","Department of Computer Science,East China University of Science and Technology,Shanghai 200237,China)"],"affiliations":[{"raw_affiliation_string":"East China University of Science and Technology, Shanghai, Shanghai, CN","institution_ids":["https://openalex.org/I143593769"]},{"raw_affiliation_string":"Department of Computer Science,East China University of Science and Technology,Shanghai 200237,China)","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100386450","display_name":"Ji Wang","orcid":"https://orcid.org/0000-0002-0724-7538"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang Ji","raw_affiliation_strings":["Department of Computer Science, East China University of Science and Technology, Shanghai, PR China","Department of Computer Science,East China University of Science and Technology,Shanghai 200237,China)"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, East China University of Science and Technology, Shanghai, PR China","institution_ids":["https://openalex.org/I143593769"]},{"raw_affiliation_string":"Department of Computer Science,East China University of Science and Technology,Shanghai 200237,China)","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007052738","display_name":"Daqi Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gao Daqi","raw_affiliation_strings":["Department of Computer Science, East China University of Science and Technology, Shanghai, PR China","Department of Computer Science,East China University of Science and Technology,Shanghai 200237,China)"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, East China University of Science and Technology, Shanghai, PR China","institution_ids":["https://openalex.org/I143593769"]},{"raw_affiliation_string":"Department of Computer Science,East China University of Science and Technology,Shanghai 200237,China)","institution_ids":["https://openalex.org/I143593769"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5109056896"],"corresponding_institution_ids":["https://openalex.org/I143593769"],"apc_list":null,"apc_paid":null,"fwci":0.5523,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.73424231,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9997000098228455,"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/T10320","display_name":"Neural Networks and Applications","score":0.9958999752998352,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9861999750137329,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.6853070259094238},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6749158501625061},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6581920385360718},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5623764991760254},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4904741942882538},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.47744446992874146},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.46456682682037354},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.45214682817459106},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4465039074420929},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4406142830848694},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42407748103141785},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.4223543405532837},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42085549235343933},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.4127694070339203},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3614237308502197},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.30164965987205505}],"concepts":[{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.6853070259094238},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6749158501625061},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6581920385360718},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5623764991760254},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4904741942882538},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.47744446992874146},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.46456682682037354},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.45214682817459106},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4465039074420929},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4406142830848694},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42407748103141785},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.4223543405532837},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42085549235343933},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.4127694070339203},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3614237308502197},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.30164965987205505},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2015.7280792","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2015.7280792","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1496317909","https://openalex.org/W1506281249","https://openalex.org/W1912982817","https://openalex.org/W1965894730","https://openalex.org/W1975619936","https://openalex.org/W1985442349","https://openalex.org/W1996932677","https://openalex.org/W2020502398","https://openalex.org/W2027678871","https://openalex.org/W2036255459","https://openalex.org/W2041162724","https://openalex.org/W2052097982","https://openalex.org/W2083249151","https://openalex.org/W2087240369","https://openalex.org/W2087787741","https://openalex.org/W2096451472","https://openalex.org/W2110518784","https://openalex.org/W2119498311","https://openalex.org/W2125607229","https://openalex.org/W2125642594","https://openalex.org/W2132423576","https://openalex.org/W2155653793","https://openalex.org/W2160133692","https://openalex.org/W2161739581","https://openalex.org/W2170860445","https://openalex.org/W2171428093","https://openalex.org/W2182722412","https://openalex.org/W3120740533","https://openalex.org/W4244494905"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W2362114017","https://openalex.org/W3147024994","https://openalex.org/W2063246903","https://openalex.org/W2374055396","https://openalex.org/W1978302214","https://openalex.org/W2021817983","https://openalex.org/W3008559849","https://openalex.org/W2371177901"],"abstract_inverted_index":{"A":[0],"pseudo-inverse":[1],"linear":[2,11],"discriminants":[3],"has":[4],"nothing":[5],"in":[6],"common":[7],"with":[8,78],"a":[9,30],"Fisher":[10],"discriminant":[12],"(FLD)":[13],"if":[14],"the":[15,24,51,63,70,76,90,97],"desired":[16,26],"outputs":[17,27],"of":[18,62],"each":[19],"sample":[20,42],"are":[21,47],"changeable.":[22],"With":[23],"customarily":[25],"{1,":[28],"-1},":[29],"simple":[31],"and":[32,44,50,84,87],"size-related":[33],"threshold":[34],"is":[35],"acquired,":[36],"which.":[37],"Multiple":[38],"thresholds":[39,80],"related":[40],"to":[41],"sizes":[43],"distribution":[45],"regions":[46],"thus":[48],"developed,":[49],"optimal":[52,79],"ones":[53],"may":[54],"be":[55],"singled":[56],"out":[57],"from":[58],"among":[59,96],"by":[60],"means":[61],"OCA":[64],"criterions.":[65],"Enormous":[66],"experimental":[67],"results":[68],"for":[69,93],"benchmark":[71],"datasets":[72,95],"have":[73,81],"verified":[74],"that":[75],"PILDs":[77],"good":[82],"learning":[83],"generalization":[85],"performances,":[86],"even":[88],"reach":[89],"top":[91],"OCAs":[92],"some":[94],"existing":[98],"classifiers.":[99]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}