Effects of Exploration Weight and Overtuned Kernel Parameters on Gaussian Process-Based Bayesian Optimization Search Performance

Gaussian process-based Bayesian optimization (GPBO) is used to search parameters in machine learning, material design, etc. It is a method for finding optimal solutions in a search space through the following four procedures. (1) Develop a Gaussian process regression (GPR) model using observed data....

Full description

Bibliographic Details
Published in:Mathematics
Main Author: Yuto Omae
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Subjects:
machine learning
Bayesian optimization
Gaussian process
overfitting
Online Access:https://www.mdpi.com/2227-7390/11/14/3067

Internet

https://www.mdpi.com/2227-7390/11/14/3067

Similar Items