{"id":"https://openalex.org/W2293704547","doi":"https://doi.org/10.1109/ijcnn.2013.6707026","title":"Random brains","display_name":"Random brains","publication_year":2013,"publication_date":"2013-08-01","ids":{"openalex":"https://openalex.org/W2293704547","doi":"https://doi.org/10.1109/ijcnn.2013.6707026","mag":"2293704547"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2013.6707026","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2013.6707026","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2013 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/A5103036745","display_name":"Ulf Johansson","orcid":"https://orcid.org/0000-0003-0412-6199"},"institutions":[{"id":"https://openalex.org/I992397","display_name":"University of Bor\u00e5s","ror":"https://ror.org/01fdxwh83","country_code":"SE","type":"education","lineage":["https://openalex.org/I992397"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Ulf Johansson","raw_affiliation_strings":["School of Business and IT, University of Bor\u00e5s, Sweden"],"affiliations":[{"raw_affiliation_string":"School of Business and IT, University of Bor\u00e5s, Sweden","institution_ids":["https://openalex.org/I992397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073489496","display_name":"Tuve L\u00f6fstr\u00f6m","orcid":"https://orcid.org/0000-0003-0274-9026"},"institutions":[{"id":"https://openalex.org/I992397","display_name":"University of Bor\u00e5s","ror":"https://ror.org/01fdxwh83","country_code":"SE","type":"education","lineage":["https://openalex.org/I992397"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Tuve Lofstrom","raw_affiliation_strings":["School of Business and IT, University of Bor\u00e5s, Sweden"],"affiliations":[{"raw_affiliation_string":"School of Business and IT, University of Bor\u00e5s, Sweden","institution_ids":["https://openalex.org/I992397"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033008105","display_name":"Henrik Bostr\u00f6m","orcid":"https://orcid.org/0000-0001-8382-0300"},"institutions":[{"id":"https://openalex.org/I161593684","display_name":"Stockholm University","ror":"https://ror.org/05f0yaq80","country_code":"SE","type":"education","lineage":["https://openalex.org/I161593684"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Henrik Bostrom","raw_affiliation_strings":["Department of Computer and Systems Sciences, Stockholm University, Sweden"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Systems Sciences, Stockholm University, Sweden","institution_ids":["https://openalex.org/I161593684"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103036745"],"corresponding_institution_ids":["https://openalex.org/I992397"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.15072377,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"7","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9995999932289124,"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/T10320","display_name":"Neural Networks and Applications","score":0.9995999932289124,"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/T10057","display_name":"Face and Expression Recognition","score":0.9940000176429749,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9915000200271606,"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/random-forest","display_name":"Random forest","score":0.7892000675201416},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6981309056282043},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6620135307312012},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5961984992027283},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5948792695999146},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5882999897003174},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5327420830726624},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.496662437915802},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47937634587287903},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.45953986048698425},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.413139283657074},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3927803039550781},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19988712668418884}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7892000675201416},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6981309056282043},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6620135307312012},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5961984992027283},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5948792695999146},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5882999897003174},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5327420830726624},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.496662437915802},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47937634587287903},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.45953986048698425},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.413139283657074},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3927803039550781},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19988712668418884},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2013.6707026","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2013.6707026","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2013 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W122801842","https://openalex.org/W1496929357","https://openalex.org/W1534477342","https://openalex.org/W1565746575","https://openalex.org/W1578627936","https://openalex.org/W1586305629","https://openalex.org/W1966693523","https://openalex.org/W1974758710","https://openalex.org/W1991418450","https://openalex.org/W2027902935","https://openalex.org/W2058307353","https://openalex.org/W2061119986","https://openalex.org/W2061554433","https://openalex.org/W2100805904","https://openalex.org/W2113242816","https://openalex.org/W2115629999","https://openalex.org/W2122892819","https://openalex.org/W2135293965","https://openalex.org/W2167055186","https://openalex.org/W2168046285","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W3120740533","https://openalex.org/W4212883601","https://openalex.org/W6604919213"],"related_works":["https://openalex.org/W2889302474","https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W2981877337","https://openalex.org/W4387048144","https://openalex.org/W3203938600"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"introduce":[4],"and":[5,37,58,93],"evaluate":[6],"a":[7,48],"novel":[8],"method,":[9,20],"called":[10],"random":[11,27,87],"brains,":[12],"for":[13,42,114],"producing":[14],"neural":[15,101],"network":[16],"ensembles.":[17],"The":[18,77,107],"suggested":[19],"which":[21],"is":[22,119],"heavily":[23],"inspired":[24],"by":[25,33,128],"the":[26,55,59,111,115,120,129,132],"forest":[28],"technique,":[29],"produces":[30],"diversity":[31,134],"implicitly":[32],"using":[34],"bootstrap":[35],"training":[36],"randomized":[38,105],"architectures.":[39,106],"More":[40],"specifically,":[41],"each":[43],"base":[44,75],"classifier":[45],"multilayer":[46],"perceptron,":[47],"number":[49],"of":[50,99],"randomly":[51],"selected":[52],"links":[53],"between":[54],"input":[56],"layer":[57,61],"hidden":[60],"are":[62],"removed":[63],"prior":[64],"to":[65,96,122],"training,":[66],"thus":[67],"resulting":[68],"in":[69,131],"potentially":[70],"weaker":[71],"but":[72],"more":[73],"diverse":[74],"classifiers.":[76],"experimental":[78],"results":[79],"on":[80],"20":[81],"UCI":[82],"data":[83],"sets":[84],"show":[85],"that":[86,110],"brains":[88],"obtained":[89],"significantly":[90],"higher":[91],"accuracy":[92],"AUC,":[94],"compared":[95],"standard":[97],"bagging":[98],"similar":[100],"networks":[102],"not":[103],"utilizing":[104],"analysis":[108],"shows":[109],"main":[112],"reason":[113],"increased":[116],"ensemble":[117],"performance":[118],"ability":[121],"produce":[123],"effective":[124],"diversity,":[125],"as":[126],"indicated":[127],"increase":[130],"difficulty":[133],"measure.":[135]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}
