How to optimize the log gabor parameters using bayesian optimization?
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I am currently working in gender classification. i've used 2D log gobor to extract the features. i came across a paper titled "Automated gait‑based gender identification using fuzzy local binary patterns with tuned parameters". They have hyper tuned the radius and threshold parameter. so i am planning to hyper tune the scale an orientation parameter in 2D log gabor using bayseian optimization. can anyone help me with the bayesian optimization code where the scale n orientation is given as an input. The inbuilt function bayesopt deals with optimizing the classifier.. Thanks in advance
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2019-11-14
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2021-8-20
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