Publication: SVM for sketch recognition: which hyperparameter interval to try?
dc.contributor.department | Department of Computer Engineering | |
dc.contributor.department | Graduate School of Sciences and Engineering | |
dc.contributor.kuauthor | Çakmak, Şerike | |
dc.contributor.kuauthor | Şen, Cansu | |
dc.contributor.kuauthor | Sezgin, Tevfik Metin | |
dc.contributor.kuauthor | Yeşilbek, Kemal Tuğrul | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.contributor.schoolcollegeinstitute | GRADUATE SCHOOL OF SCIENCES AND ENGINEERING | |
dc.date.accessioned | 2024-11-09T22:56:56Z | |
dc.date.issued | 2015 | |
dc.description.abstract | Hyperparameters are among the most crucial factors that effect the performance of machine learning algorithms. Since there is not a common ground on which hyperparameter combinations give the highest performance in terms of prediction accuracy, hyperparameter search needs to be conducted each time a model is to be trained. in this work, we analyzed how similar hyperparemeters perform on various datasets from sketch recognition domain. Results have shown that hyperparameter search space can be reduced to a subspace despite differences in dataset characteristics. | |
dc.description.indexedby | WOS | |
dc.description.openaccess | NO | |
dc.description.publisherscope | International | |
dc.description.sponsoredbyTubitakEu | N/A | |
dc.identifier.isbn | 978-1-4673-7386-9 | |
dc.identifier.issn | 2165-0608 | |
dc.identifier.quartile | N/A | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/7467 | |
dc.identifier.wos | 380500900216 | |
dc.keywords | Hyperparameter search | |
dc.keywords | Sketch data | |
dc.keywords | Grid search | |
dc.keywords | Cross validation | |
dc.keywords | Support vector machines | |
dc.language.iso | tur | |
dc.publisher | IEEE | |
dc.relation.ispartof | 2015 23rd Signal Processing and Communications Applications Conference (Siu) | |
dc.subject | Civil engineering | |
dc.subject | Electrical electronics engineering | |
dc.subject | Telecommunication | |
dc.title | SVM for sketch recognition: which hyperparameter interval to try? | |
dc.type | Conference Proceeding | |
dspace.entity.type | Publication | |
local.contributor.kuauthor | Yeşilbek, Kemal Tuğrul | |
local.contributor.kuauthor | Şen, Cansu | |
local.contributor.kuauthor | Çakmak, Şerike | |
local.contributor.kuauthor | Sezgin, Tevfik Metin | |
local.publication.orgunit1 | GRADUATE SCHOOL OF SCIENCES AND ENGINEERING | |
local.publication.orgunit1 | College of Engineering | |
local.publication.orgunit2 | Department of Computer Engineering | |
local.publication.orgunit2 | Graduate School of Sciences and Engineering | |
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