{"id":"https://openalex.org/W4313400923","doi":"https://doi.org/10.1007/978-981-19-5170-1_10","title":"Case Study III: Tuning of Deep Neural Networks","display_name":"Case Study III: Tuning of Deep Neural Networks","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4313400923","doi":"https://doi.org/10.1007/978-981-19-5170-1_10"},"language":"en","primary_location":{"id":"doi:10.1007/978-981-19-5170-1_10","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-981-19-5170-1_10","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-981-19-5170-1_10.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Hyperparameter Tuning for Machine and Deep Learning with R","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/978-981-19-5170-1_10.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020539256","display_name":"Thomas Bartz\u2013Beielstein","orcid":"https://orcid.org/0000-0002-5938-5158"},"institutions":[{"id":"https://openalex.org/I102520234","display_name":"TH K\u00f6ln - University of Applied Sciences","ror":"https://ror.org/014nnvj65","country_code":"DE","type":"education","lineage":["https://openalex.org/I102520234"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Thomas Bartz-Beielstein","raw_affiliation_strings":["Institute for Data Science, Engineering and Analytics, TH K\u00f6ln, Gummersbach, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Data Science, Engineering and Analytics, TH K\u00f6ln, Gummersbach, Germany","institution_ids":["https://openalex.org/I102520234"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063401368","display_name":"Sowmya Chandrasekaran","orcid":"https://orcid.org/0000-0002-5304-6411"},"institutions":[{"id":"https://openalex.org/I102520234","display_name":"TH K\u00f6ln - University of Applied Sciences","ror":"https://ror.org/014nnvj65","country_code":"DE","type":"education","lineage":["https://openalex.org/I102520234"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sowmya Chandrasekaran","raw_affiliation_strings":["Institute for Data Science, Engineering and Analytics, TH K\u00f6ln, Gummersbach, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Data Science, Engineering and Analytics, TH K\u00f6ln, Gummersbach, Germany","institution_ids":["https://openalex.org/I102520234"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074567485","display_name":"Frederik Rehbach","orcid":"https://orcid.org/0000-0003-0922-8629"},"institutions":[{"id":"https://openalex.org/I102520234","display_name":"TH K\u00f6ln - University of Applied Sciences","ror":"https://ror.org/014nnvj65","country_code":"DE","type":"education","lineage":["https://openalex.org/I102520234"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Frederik Rehbach","raw_affiliation_strings":["Institute for Data Science, Engineering and Analytics, TH K\u00f6ln, Gummersbach, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Data Science, Engineering and Analytics, TH K\u00f6ln, Gummersbach, Germany","institution_ids":["https://openalex.org/I102520234"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5020539256"],"corresponding_institution_ids":["https://openalex.org/I102520234"],"apc_list":null,"apc_paid":null,"fwci":1.4964,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.81070943,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"235","last_page":"269"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.36399999260902405,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.36399999260902405,"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/T10320","display_name":"Neural Networks and Applications","score":0.34369999170303345,"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/hyperparameter","display_name":"Hyperparameter","score":0.9778648614883423},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7388038039207458},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6633191108703613},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.6630920171737671},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6224972009658813},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.6204491257667542},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5864726305007935},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5244776606559753},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.05373319983482361}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.9778648614883423},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7388038039207458},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6633191108703613},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.6630920171737671},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6224972009658813},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.6204491257667542},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5864726305007935},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5244776606559753},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.05373319983482361}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-981-19-5170-1_10","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-981-19-5170-1_10","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-981-19-5170-1_10.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Hyperparameter Tuning for Machine and Deep Learning with R","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-981-19-5170-1_10","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-981-19-5170-1_10","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-981-19-5170-1_10.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Hyperparameter Tuning for Machine and Deep Learning with R","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4313400923.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2140186469","https://openalex.org/W4390421286","https://openalex.org/W4280563792","https://openalex.org/W4389724018","https://openalex.org/W4318719684","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W4315865067","https://openalex.org/W3208304128"],"abstract_inverted_index":{"Abstract":[0],"A":[1],"surrogate":[2],"model":[3],"based":[4],"Hyperparameter":[5],"Tuning":[6],"(HPT)":[7],"approach":[8],"for":[9,51,123],"Deep":[10,24],"Learning":[11,92],"(DL)":[12],"is":[13,42,119],"presented.":[14],"This":[15,107],"chapter":[16],"demonstrates":[17],"how":[18],"the":[19,39,48,55,89,102,105,113,124],"architecture-level":[20],"parameters":[21],"(hyperparameters)":[22],"of":[23,38,80,88,115,120],"Neural":[25],"Networks":[26],"(DNNs)":[27],"that":[28],"were":[29],"implemented":[30],"in":[31,65,75,96,112],"/":[32],"can":[33,62],"be":[34,63,73],"optimized.":[35],"The":[36,78,86],"implementation":[37],"tuning":[40],"procedure":[41],"100%":[43],"accessible":[44],"from":[45,104],"R":[46],",":[47,59],"software":[49,56],"environment":[50],"statistical":[52],"computing.":[53],"How":[54],"packages":[57],"(,":[58],"and":[60,69],")":[61],"combined":[64],"a":[66,81],"very":[67],"efficient":[68],"effective":[70],"manner":[71],"will":[72],"exemplified":[74],"this":[76,97],"chapter.":[77],"hyperparameters":[79],"standard":[82],"DNN":[83],"are":[84,99],"tuned.":[85],"performances":[87],"six":[90],"Machine":[91],"(ML)":[93],"methods":[94],"discussed":[95],"book":[98],"compared":[100],"to":[101],"results":[103],"DNN.":[106],"study":[108],"provides":[109],"valuable":[110],"insights":[111],"tunability":[114],"several":[116],"methods,":[117],"which":[118],"great":[121],"importance":[122],"practitioner.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}
