COMPARATIVE STUDY OF SURROGATE TECHNIQUES FOR HYPERPARAMETER OPTIMIZATION IN CONVOLUTIONAL NEURAL NETWORK
Optimizing hyperparameters in CNN is tedious for many researchers and practitioners. it requires a high degree of expertise or a lot of experience to optimize the hyperparameter and such manual optimization is likely to be biased. Hyperparameters in deep learning can be divided into two types which...
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| 第一著者: | |
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| フォーマット: | 学位論文 |
| 言語: | English |
| 出版事項: |
2023
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| 主題: | |
| オンライン･アクセス: | http://utpedia.utp.edu.my/id/eprint/24632/1/NurshazlynMohdAszemi_17007352.pdf http://utpedia.utp.edu.my/id/eprint/24632/ |
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