{"id":"https://openalex.org/W4243138158","doi":"https://doi.org/10.1007/978-3-030-05318-5_5","title":"Hyperopt-Sklearn","display_name":"Hyperopt-Sklearn","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W4243138158","doi":"https://doi.org/10.1007/978-3-030-05318-5_5"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-030-05318-5_5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-030-05318-5_5","pdf_url":"https://link.springer.com/content/pdf/10.1007%2F978-3-030-05318-5_5.pdf","source":{"id":"https://openalex.org/S4210189751","display_name":"\u0098The \u009cSpringer series on challenges in machine learning","issn_l":"2520-131X","issn":["2520-131X","2520-1328"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Springer Series on Challenges in Machine Learning","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007%2F978-3-030-05318-5_5.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041027747","display_name":"Brent Komer","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Brent Komer","raw_affiliation_strings":["Center for Theoretical Neuroscience, University of Waterloo, Waterloo, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Center for Theoretical Neuroscience, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057264590","display_name":"James Bergstra","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"James Bergstra","raw_affiliation_strings":["Center for Theoretical Neuroscience, University of Waterloo, Waterloo, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Center for Theoretical Neuroscience, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055630059","display_name":"Chris Eliasmith","orcid":"https://orcid.org/0000-0003-2933-0209"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Chris Eliasmith","raw_affiliation_strings":["Center for Theoretical Neuroscience, University of Waterloo, Waterloo, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Center for Theoretical Neuroscience, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5041027747"],"corresponding_institution_ids":["https://openalex.org/I151746483"],"apc_list":null,"apc_paid":null,"fwci":5.7839,"has_fulltext":true,"cited_by_count":56,"citation_normalized_percentile":{"value":0.97360176,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"97","last_page":"111"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":1.0,"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":1.0,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9979000091552734,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9699000120162964,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.9238194227218628},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6451568007469177},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.634555459022522},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6035946011543274},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.5219537615776062},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5061666369438171},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4963873028755188},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.4731781780719757},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.4691428542137146},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3948317766189575},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3814931809902191},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.10846063494682312},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07410410046577454}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.9238194227218628},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6451568007469177},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.634555459022522},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6035946011543274},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.5219537615776062},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5061666369438171},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4963873028755188},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4731781780719757},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.4691428542137146},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3948317766189575},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3814931809902191},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.10846063494682312},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07410410046577454},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-030-05318-5_5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-030-05318-5_5","pdf_url":"https://link.springer.com/content/pdf/10.1007%2F978-3-030-05318-5_5.pdf","source":{"id":"https://openalex.org/S4210189751","display_name":"\u0098The \u009cSpringer series on challenges in machine learning","issn_l":"2520-131X","issn":["2520-131X","2520-1328"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Springer Series on Challenges in Machine Learning","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-3-030-05318-5_5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-030-05318-5_5","pdf_url":"https://link.springer.com/content/pdf/10.1007%2F978-3-030-05318-5_5.pdf","source":{"id":"https://openalex.org/S4210189751","display_name":"\u0098The \u009cSpringer series on challenges in machine learning","issn_l":"2520-131X","issn":["2520-131X","2520-1328"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Springer Series on Challenges in Machine Learning","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1304196372","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"}],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4243138158.pdf","grobid_xml":"https://content.openalex.org/works/W4243138158.grobid-xml"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W60686164","https://openalex.org/W1994197834","https://openalex.org/W2102539288","https://openalex.org/W2112364454","https://openalex.org/W2112796928","https://openalex.org/W2127416213","https://openalex.org/W2133990480","https://openalex.org/W2141125852","https://openalex.org/W2189149359"],"related_works":["https://openalex.org/W4386603768","https://openalex.org/W2950475743","https://openalex.org/W2886711096","https://openalex.org/W2750384547","https://openalex.org/W4238897586","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W435179959","https://openalex.org/W4389249638","https://openalex.org/W2735450835"],"abstract_inverted_index":{"Hyperopt-sklearn":[0],"is":[1,92],"a":[2,40,51],"software":[3],"project":[4],"that":[5,22,54,88],"provides":[6],"automated":[7],"algorithm":[8],"configuration":[9],"of":[10,25,31,68,116],"the":[11,20,23,29,104,114],"Scikit-learn":[12],"machine":[13],"learning":[14],"library.":[15],"Following":[16],"Auto-Weka,":[17],"we":[18,98],"take":[19],"view":[21],"choice":[24,30],"classifier":[26],"and":[27,65,79,94,110],"even":[28],"preprocessing":[32],"module":[33],"can":[34],"be":[35],"taken":[36],"together":[37],"to":[38,49],"represent":[39],"single":[41],"large":[42],"hyperparameter":[43],"optimization":[44],"problem.":[45],"We":[46,72],"use":[47],"Hyperopt":[48,78],"define":[50],"search":[52,75],"space":[53,91,106],"encompasses":[55],"many":[56],"standard":[57,80],"components":[58],"(e.g.":[59],"SVM,":[60],"RF,":[61],"KNN,":[62],"PCA,":[63],"TFIDF)":[64],"common":[66],"patterns":[67],"composing":[69],"them":[70],"together.":[71],"demonstrate,":[73],"using":[74],"algorithms":[76],"in":[77],"benchmarking":[81],"data":[82],"sets":[83],"(MNIST,":[84],"20-Newsgroups,":[85],"Convex":[86,111],"Shapes),":[87],"searching":[89],"this":[90],"practical":[93],"effective.":[95],"In":[96],"particular,":[97],"improve":[99],"on":[100],"best-known":[101],"scores":[102],"for":[103,107],"model":[105],"both":[108],"MNIST":[109],"Shapes":[112],"at":[113],"time":[115],"release.":[117]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":4}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2022-05-12T00:00:00"}