{"id":"https://openalex.org/W2778356253","doi":"https://doi.org/10.1109/clei.2017.8226385","title":"Extreme learning machine prediction under high class imbalance in bioinformatics","display_name":"Extreme learning machine prediction under high class imbalance in bioinformatics","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2778356253","doi":"https://doi.org/10.1109/clei.2017.8226385","mag":"2778356253"},"language":"en","primary_location":{"id":"doi:10.1109/clei.2017.8226385","is_oa":false,"landing_page_url":"https://doi.org/10.1109/clei.2017.8226385","pdf_url":null,"source":{"id":"https://openalex.org/S4306498236","display_name":"2017 XLIII Latin American Computer Conference (CLEI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 XLIII Latin American Computer Conference (CLEI)","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/A5026729963","display_name":"Tadeo Rodriguez","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150023","display_name":"Computational Intelligence and Information Systems Lab","ror":"https://ror.org/04fqqys39","country_code":"AR","type":"facility","lineage":["https://openalex.org/I4210150023"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"T. Rodriguez","raw_affiliation_strings":["Systems and Computational Intelligence (sinc(i)), Research Institute for Signals, Argentina"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Systems and Computational Intelligence (sinc(i)), Research Institute for Signals, Argentina","institution_ids":["https://openalex.org/I4210150023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030230762","display_name":"Leandro E. Di Persia","orcid":"https://orcid.org/0000-0002-0331-6989"},"institutions":[{"id":"https://openalex.org/I4210150023","display_name":"Computational Intelligence and Information Systems Lab","ror":"https://ror.org/04fqqys39","country_code":"AR","type":"facility","lineage":["https://openalex.org/I4210150023"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"L.E. Di Persia","raw_affiliation_strings":["Systems and Computational Intelligence (sinc(i)), Research Institute for Signals, Argentina"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Systems and Computational Intelligence (sinc(i)), Research Institute for Signals, Argentina","institution_ids":["https://openalex.org/I4210150023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077266711","display_name":"Diego H. Milone","orcid":"https://orcid.org/0000-0003-2182-4351"},"institutions":[{"id":"https://openalex.org/I4210150023","display_name":"Computational Intelligence and Information Systems Lab","ror":"https://ror.org/04fqqys39","country_code":"AR","type":"facility","lineage":["https://openalex.org/I4210150023"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"D.H. Milone","raw_affiliation_strings":["Systems and Computational Intelligence (sinc(i)), Research Institute for Signals, Argentina"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Systems and Computational Intelligence (sinc(i)), Research Institute for Signals, Argentina","institution_ids":["https://openalex.org/I4210150023"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091024901","display_name":"Georgina Stegmayer","orcid":"https://orcid.org/0000-0003-4459-4560"},"institutions":[{"id":"https://openalex.org/I4210150023","display_name":"Computational Intelligence and Information Systems Lab","ror":"https://ror.org/04fqqys39","country_code":"AR","type":"facility","lineage":["https://openalex.org/I4210150023"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"G. Stegmayer","raw_affiliation_strings":["Systems and Computational Intelligence (sinc(i)), Research Institute for Signals, Argentina"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Systems and Computational Intelligence (sinc(i)), Research Institute for Signals, Argentina","institution_ids":["https://openalex.org/I4210150023"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210150023"],"apc_list":null,"apc_paid":null,"fwci":0.1384,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46438997,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"16","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9998000264167786,"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/T10062","display_name":"MicroRNA in disease regulation","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"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/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"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/machine-learning","display_name":"Machine learning","score":0.8327879905700684},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8034858703613281},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7614589929580688},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.6726110577583313},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6446855068206787},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5708171129226685},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5687639117240906}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.8327879905700684},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8034858703613281},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7614589929580688},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.6726110577583313},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6446855068206787},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5708171129226685},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5687639117240906}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/clei.2017.8226385","is_oa":false,"landing_page_url":"https://doi.org/10.1109/clei.2017.8226385","pdf_url":null,"source":{"id":"https://openalex.org/S4306498236","display_name":"2017 XLIII Latin American Computer Conference (CLEI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 XLIII Latin American Computer Conference (CLEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W144423133","https://openalex.org/W264323048","https://openalex.org/W1565746575","https://openalex.org/W1648301895","https://openalex.org/W1751389566","https://openalex.org/W1850407572","https://openalex.org/W1878848198","https://openalex.org/W1920564293","https://openalex.org/W1978578227","https://openalex.org/W1984385688","https://openalex.org/W1991181258","https://openalex.org/W1991244466","https://openalex.org/W2017426710","https://openalex.org/W2024223694","https://openalex.org/W2032323486","https://openalex.org/W2040263621","https://openalex.org/W2042996013","https://openalex.org/W2046084401","https://openalex.org/W2046240326","https://openalex.org/W2076422568","https://openalex.org/W2099454382","https://openalex.org/W2106144124","https://openalex.org/W2106348976","https://openalex.org/W2107146952","https://openalex.org/W2109574129","https://openalex.org/W2114973325","https://openalex.org/W2120583228","https://openalex.org/W2134603844","https://openalex.org/W2136846651","https://openalex.org/W2140751493","https://openalex.org/W2142878546","https://openalex.org/W2148143831","https://openalex.org/W2149308034","https://openalex.org/W6656767711","https://openalex.org/W6682141768"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W31566076","https://openalex.org/W4297902562","https://openalex.org/W2741186499","https://openalex.org/W2804652951","https://openalex.org/W2556335056","https://openalex.org/W2002678693","https://openalex.org/W1584764049","https://openalex.org/W2743832667","https://openalex.org/W2969890106"],"abstract_inverted_index":{"Class":[0],"imbalance":[1,67,76,87,132,165],"in":[2,16,28,50,107,133,137,182],"machine":[3,82],"learning":[4,83,115],"is":[5,24,71,96],"when":[6],"there":[7,23],"are":[8,45,140],"significantly":[9],"fewer":[10],"training":[11],"instances":[12],"of":[13,32,55,57,112,159,173],"one":[14],"class":[15,66,75,131,164],"comparison":[17,51],"to":[18,52,127,146],"another":[19],"one.":[20],"In":[21,119],"bioinformatics,":[22],"such":[25],"a":[26,37,48,64,97,124],"problem":[27],"the":[29,53,86,108,129,160,171,174,183],"computational":[30],"prediction":[31,135],"novel":[33,125],"microRNA":[34],"(miRNAs)":[35],"within":[36],"full":[38],"genome.":[39],"The":[40,167],"well-known":[41,72],"precursors":[42],"miRNA":[43],"(pre-miRNA)":[44],"usually":[46,77],"only":[47],"few":[49],"hundreds":[54],"thousands":[56],"potential":[58],"candidates,":[59],"which":[60,138],"makes":[61],"this":[62,120],"task":[63],"high":[65,74,114,130],"classification":[68],"problem.":[69],"It":[70],"that":[73,103],"affects":[78],"any":[79],"classical":[80],"supervised":[81,98],"classifier.":[84],"Thus":[85],"must":[88],"be":[89],"explicitly":[90],"considered.":[91],"Extreme":[92],"Learning":[93],"Machine":[94],"(ELM)":[95],"artificial":[99],"neural":[100],"network":[101],"model":[102],"has":[104],"gained":[105],"interest":[106],"last":[109],"years":[110],"because":[111],"its":[113],"rate":[116],"and":[117],"performance.":[118],"work,":[121],"we":[122],"propose":[123],"approach":[126,176],"overcome":[128],"pre-miRNAs":[134],"data":[136,151],"ELMs":[139],"used":[141,156],"for":[142,157],"predicting":[143],"good":[144],"candidates":[145],"pre-miRNA,":[147],"without":[148],"needing":[149],"balanced":[150],"sets.":[152],"Real":[153],"datasets":[154],"were":[155],"validation":[158],"proposal":[161],"with":[162],"several":[163],"levels.":[166],"results":[168],"obtained":[169],"showed":[170],"superiority":[172],"ELM":[175],"against":[177],"very":[178],"recent":[179],"state-of-the-art":[180],"methods":[181],"same":[184],"experimental":[185],"conditions.":[186]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
