{"id":"https://openalex.org/W2548858661","doi":"https://doi.org/10.1109/icacci.2016.7732464","title":"A correlation based SVM-recursive multiple feature elimination classifier for breast cancer disease using microarray","display_name":"A correlation based SVM-recursive multiple feature elimination classifier for breast cancer disease using microarray","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2548858661","doi":"https://doi.org/10.1109/icacci.2016.7732464","mag":"2548858661"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2016.7732464","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2016.7732464","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5100600879","display_name":"K R Kavitha","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"K R Kavitha","raw_affiliation_strings":["Department of Computer Science and Applications, Amrita University, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Applications, Amrita University, India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032422606","display_name":"Gayathri Rajendran","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"G Syamili Rajendran","raw_affiliation_strings":["Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, IN"],"affiliations":[{"raw_affiliation_string":"Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, IN","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079417792","display_name":"J Varsha","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"J Varsha","raw_affiliation_strings":["Department of Computer Science and Applications, Amrita University, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Applications, Amrita University, India","institution_ids":["https://openalex.org/I81556334"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100600879"],"corresponding_institution_ids":["https://openalex.org/I81556334"],"apc_list":null,"apc_paid":null,"fwci":2.0008,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.86920841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9611999988555908,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9117000102996826,"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/support-vector-machine","display_name":"Support vector machine","score":0.8415683507919312},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6121910214424133},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5965648889541626},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.540510356426239},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4761383831501007},{"id":"https://openalex.org/keywords/microarray-analysis-techniques","display_name":"Microarray analysis techniques","score":0.44229888916015625},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42441990971565247},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3608510494232178},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3420957326889038},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.24796682596206665},{"id":"https://openalex.org/keywords/gene-expression","display_name":"Gene expression","score":0.11325019598007202},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.0883844792842865},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.06111779808998108}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8415683507919312},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6121910214424133},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5965648889541626},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.540510356426239},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4761383831501007},{"id":"https://openalex.org/C8415881","wikidata":"https://www.wikidata.org/wiki/Q6839217","display_name":"Microarray analysis techniques","level":4,"score":0.44229888916015625},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42441990971565247},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3608510494232178},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3420957326889038},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.24796682596206665},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.11325019598007202},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0883844792842865},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.06111779808998108},{"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":1,"locations":[{"id":"doi:10.1109/icacci.2016.7732464","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2016.7732464","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1968461733","https://openalex.org/W2006937300","https://openalex.org/W2045761815","https://openalex.org/W2068474065","https://openalex.org/W2068497347","https://openalex.org/W2095365800","https://openalex.org/W2106483643","https://openalex.org/W2118142823","https://openalex.org/W2119094039","https://openalex.org/W2131105131","https://openalex.org/W2156070874","https://openalex.org/W2159048517","https://openalex.org/W2416438111"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2012353789","https://openalex.org/W2530420969","https://openalex.org/W2051187167","https://openalex.org/W1980100242"],"abstract_inverted_index":{"Support":[0,205],"Vector":[1,206],"Machine":[2,207],"(SVM)":[3],"[2],":[4],"is":[5,72,76,97,202],"most":[6,61],"widely":[7],"popular":[8],"learning":[9],"algorithm":[10,63,96,138,155,213,237],"used":[11],"for":[12,24,57,68],"classification":[13,69,89,244],"of":[14,41,53,70,90,108,149,196],"large":[15,39],"dataset.":[16,92],"Our":[17],"project":[18],"aims":[19],"to":[20,49,131,231],"generate":[21,232],"a":[22,38,182,217,233],"classifier":[23],"breast":[25,34],"cancer":[26,35],"genes":[27,42,54,126,145,179,219,223],"microarray":[28,36,71,123],"by":[29],"using":[30],"modified-SVM-RFE":[31],"algorithm.":[32,151],"This":[33,235],"contains":[37,124],"number":[40,52],"and":[43,111,180,188,227,249],"its":[44,127,250],"expression,":[45],"so":[46,241],"it":[47,160],"necessary":[48],"reduce":[50,132],"the":[51,60,91,106,109,133,136,164,177,186,193,243],"before":[55,168],"applying":[56,169],"classification.":[58],"So":[59,135,167,198],"efficient":[62],"that":[64,242],"can":[65,246,252],"be":[66,247,253],"applied":[67],"SVM-RFE":[73,104,150,191],"[3][8],":[74],"which":[75,80,139,214],"an":[77],"embedded":[78],"method,":[79],"performs":[81],"backward":[82],"single":[83,147],"gene":[84,184,226],"elimination":[85],"as":[86,88],"well":[87],"A":[93],"new":[94,183,194,218],"modified":[95,137],"proposed":[98,200],"with":[99],"less":[100],"computation":[101],"over":[102],"SVM-RFE.":[103],"generates":[105],"rank":[107,115],"features":[110],"eliminates":[112],"one":[113,143],"lowest":[114],"irrelevant":[116,144,158],"feature,":[117],"in":[118,146],"each":[119],"iteration.":[120],"Since":[121],"our":[122,171,199],"47,294":[125],"very":[128],"computational":[129],"overhead":[130],"dimension.":[134],"removes":[140,157],"more":[141],"than":[142],"iteration":[148],"And":[152],"also":[153],"this":[154],"only":[156],"gene,":[159],"does":[161],"not":[162],"remove":[163],"correlated":[165,178,222],"genes.":[166,197],"SVM-RFE,":[170],"research":[172],"focuses":[173],"on":[174,192],"finding":[175],"out":[176],"extracting":[181],"from":[185,220],"two,":[187],"then":[189,228],"apply":[190,229],"set":[195],"method":[201],"Correlation":[203],"based":[204],"Recursive":[208],"Multiple":[209],"Feature":[210],"Elimination":[211],"(CSVM-RMFE)":[212],"first":[215],"extracts":[216],"two":[221],"called":[224],"virtual":[225],"SVM-RMFE":[230,236],"classifier.":[234],"eliminate":[238],"multiple":[239],"feature":[240],"time":[245],"reduced":[248],"accuracy":[251],"increased.":[254]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
