Performance Evaluation of Classification Algorithms Using Hyperparameter Optimization
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Classification problems have an important role in the field of machine learning and data mining. Classification problems are used in different areas such as disease diagnosis, estimation of bank customers, drug studies, sentiment analysis. Many classification algorithms have been developed in the literature and these algorithms have many different parameter inputs. In this study, it is aimed to increase the classification success by using hyperparameter optimization algorithms. K-nearest neighbor, support vector machines, decision tree and gradient boosting classification algorithms were applied to the frequently used 'heart and iris' datasets in the literature. Grid search and random search algorithms, which are hyperparameter optimization algorithms, are applied to these selected classification algorithms. As a result of the experimental studies, it has been observed that the accuracy of all classification algorithms increases when hyperparameter optimization algorithms are applied. The parameter values that give the best results are shown. © 2021 IEEE
Açıklama
6th International Conference on Computer Science and Engineering, UBMK 2021 -- 15 September 2021 through 17 September 2021 -- -- 176826
Anahtar Kelimeler
Classification Algorithms, Hyperparameter Optimization, Machine Learning, Optimization, Supervised Learning, Computer aided diagnosis, Data mining, Decision trees, Nearest neighbor search, Sentiment analysis, Support vector machines, Classification algorithm, Disease diagnosis, Hyper-parameter optimizations, Machine-learning, Nearest-neighbour, Optimisations, Optimization algorithms, Performances evaluation, Sentiment analysis, Supervised learning, Classification (of information)
Kaynak
Proceedings - 6th International Conference on Computer Science and Engineering, UBMK 2021
WoS Q Değeri
Scopus Q Değeri
N/A
