{"id":"https://openalex.org/W2897131745","doi":"https://doi.org/10.1109/ijcnn.2018.8488992","title":"A novel statistical based feature extraction approach for the inner-class feature estimation using linear regression","display_name":"A novel statistical based feature extraction approach for the inner-class feature estimation using linear regression","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2897131745","doi":"https://doi.org/10.1109/ijcnn.2018.8488992","mag":"2897131745"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2018.8488992","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8488992","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-02423377","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069997503","display_name":"Fannia Pacheco","orcid":"https://orcid.org/0000-0001-6997-0222"},"institutions":[{"id":"https://openalex.org/I144889574","display_name":"Universit\u00e9 de Pau et des Pays de l'Adour","ror":"https://ror.org/01frn9647","country_code":"FR","type":"education","lineage":["https://openalex.org/I144889574"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Fannia Pacheco","raw_affiliation_strings":["UNIV PAU & PAYS ADOUR, LIUPPA, ANGLET, France"],"affiliations":[{"raw_affiliation_string":"UNIV PAU & PAYS ADOUR, LIUPPA, ANGLET, France","institution_ids":["https://openalex.org/I144889574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087889711","display_name":"Ernesto Exp\u00f3sito","orcid":"https://orcid.org/0000-0002-3543-2909"},"institutions":[{"id":"https://openalex.org/I144889574","display_name":"Universit\u00e9 de Pau et des Pays de l'Adour","ror":"https://ror.org/01frn9647","country_code":"FR","type":"education","lineage":["https://openalex.org/I144889574"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Ernesto Exposito","raw_affiliation_strings":["UNIV PAU & PAYS ADOUR, LIUPPA, ANGLET, France"],"affiliations":[{"raw_affiliation_string":"UNIV PAU & PAYS ADOUR, LIUPPA, ANGLET, France","institution_ids":["https://openalex.org/I144889574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042045106","display_name":"Jos\u00e9 Aguilar","orcid":"https://orcid.org/0000-0003-4194-6882"},"institutions":[{"id":"https://openalex.org/I144889574","display_name":"Universit\u00e9 de Pau et des Pays de l'Adour","ror":"https://ror.org/01frn9647","country_code":"FR","type":"education","lineage":["https://openalex.org/I144889574"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jose Aguilar","raw_affiliation_strings":["UNIV PAU & PAYS ADOUR, LIUPPA, ANGLET, France"],"affiliations":[{"raw_affiliation_string":"UNIV PAU & PAYS ADOUR, LIUPPA, ANGLET, France","institution_ids":["https://openalex.org/I144889574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064681782","display_name":"Mathieu Gineste","orcid":null},"institutions":[{"id":"https://openalex.org/I4210140930","display_name":"Thales (France)","ror":"https://ror.org/04emwm605","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210140930"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mathieu Gineste","raw_affiliation_strings":["Thales Alenia Space, TOULOUSE, France"],"affiliations":[{"raw_affiliation_string":"Thales Alenia Space, TOULOUSE, France","institution_ids":["https://openalex.org/I4210140930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055442420","display_name":"C\u00e9dric Baudoin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210140930","display_name":"Thales (France)","ror":"https://ror.org/04emwm605","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210140930"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Cedric Baudoin","raw_affiliation_strings":["Thales Alenia Space, TOULOUSE, France"],"affiliations":[{"raw_affiliation_string":"Thales Alenia Space, TOULOUSE, France","institution_ids":["https://openalex.org/I4210140930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5069997503"],"corresponding_institution_ids":["https://openalex.org/I144889574"],"apc_list":null,"apc_paid":null,"fwci":0.5536,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.70938233,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"15","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994999766349792,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/computer-science","display_name":"Computer science","score":0.6991571187973022},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6610838174819946},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5883321166038513},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.5760722756385803},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5658226609230042},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5269551873207092},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4825950860977173},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4823562502861023},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43800121545791626},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.4288191497325897},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4146486222743988},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1808478832244873},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17769533395767212}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6991571187973022},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6610838174819946},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5883321166038513},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.5760722756385803},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5658226609230042},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5269551873207092},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4825950860977173},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4823562502861023},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43800121545791626},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.4288191497325897},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4146486222743988},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1808478832244873},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17769533395767212},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2018.8488992","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8488992","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-02423377v1","is_oa":true,"landing_page_url":"https://hal.science/hal-02423377","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN), Jul 2018, Rio de Janeiro, France. pp.1-8, ⟨10.1109/IJCNN.2018.8488992⟩","raw_type":"Conference papers"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-02423377v1","is_oa":true,"landing_page_url":"https://hal.science/hal-02423377","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN), Jul 2018, Rio de Janeiro, France. pp.1-8, ⟨10.1109/IJCNN.2018.8488992⟩","raw_type":"Conference papers"},"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W988335224","https://openalex.org/W1500731913","https://openalex.org/W1524496078","https://openalex.org/W1537430301","https://openalex.org/W1554944419","https://openalex.org/W1965334909","https://openalex.org/W1985727365","https://openalex.org/W1988300964","https://openalex.org/W2023721289","https://openalex.org/W2076063813","https://openalex.org/W2106525823","https://openalex.org/W2139059558","https://openalex.org/W2148913232","https://openalex.org/W2167101736","https://openalex.org/W2171033594","https://openalex.org/W2224600518","https://openalex.org/W2255206882","https://openalex.org/W2293050121","https://openalex.org/W2313953460","https://openalex.org/W2345202467","https://openalex.org/W2534634332","https://openalex.org/W2606126501","https://openalex.org/W2770648450","https://openalex.org/W2963197767","https://openalex.org/W2963516518","https://openalex.org/W2998768810","https://openalex.org/W3121912665","https://openalex.org/W4253269957","https://openalex.org/W4292483811","https://openalex.org/W4301866626","https://openalex.org/W6631506987","https://openalex.org/W6736211447","https://openalex.org/W6744538726"],"related_works":["https://openalex.org/W3147584709","https://openalex.org/W2977677679","https://openalex.org/W1992327129","https://openalex.org/W2381986121","https://openalex.org/W2370918718","https://openalex.org/W2256933480","https://openalex.org/W2370081953","https://openalex.org/W2027854990","https://openalex.org/W4387527746","https://openalex.org/W4256548255"],"abstract_inverted_index":{"Nowadays,":[0],"statistical":[1,45,54,87,102,151,164],"based":[2,152],"feature":[3,103],"extraction":[4],"approaches":[5,30],"are":[6,19,154],"commonly":[7],"used":[8,156],"in":[9,67,135,176],"the":[10,26,36,39,71,93,109,114,121,124,163,171,174,185],"knowledge":[11],"discovery":[12],"field":[13],"with":[14,130],"Machine":[15],"Learning.":[16],"These":[17],"features":[18,153,165],"accurate":[20],"and":[21,150],"give":[22,167],"relevant":[23],"information":[24],"of":[25,38,79,95,98,123,170,173,187],"samples;":[27],"however,":[28],"these":[29,60],"consider":[31],"some":[32,180],"assumptions,":[33],"such":[34,182],"as":[35,120,183],"membership":[37],"signals":[40],"or":[41,189],"samples":[42],"to":[43,52,69,107,113,147,178],"specific":[44],"distributions.":[46],"In":[47,75,89,139,160],"this":[48,140,158,161],"work,":[49],"we":[50],"propose":[51],"model":[53],"computation":[55],"through":[56],"linear":[57,80],"regression":[58,81],"models;":[59],"models":[61,82,97],"will":[62,83,104,118],"be":[63,105,119,148],"divided":[64],"by":[65],"classes,":[66],"order":[68,177],"increase":[70],"inner-class":[72],"identification":[73],"likelihood.":[74],"general,":[76],"an":[77,90],"ensemble":[78],"estimate":[84],"a":[85,99,131],"targeted":[86,101],"feature.":[88,125],"online":[91],"deployment,":[92],"pool":[94],"LR":[96],"given":[100],"evaluated":[106],"find":[108],"most":[110],"similar":[111],"value":[112],"current":[115],"input,":[116],"which":[117],"estimated":[122],"The":[126],"proposal":[127],"is":[128],"tested":[129],"real":[132],"world":[133],"application":[134],"traffic":[136],"network":[137,175],"classification.":[138],"case":[141],"study,":[142],"fast":[143],"classification":[144],"response":[145],"has":[146],"provided,":[149],"widely":[155],"for":[157],"aim.":[159],"sense,":[162],"must":[166],"early":[168],"signs":[169],"status":[172],"achieve":[179],"objectives":[181],"improve":[184],"quality":[186],"service":[188],"detect":[190],"malicious":[191],"traffic.":[192]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}