Work

Verifying the Effect of Initial Sample Size in Bayesian Optimization

Year: 2024

Type: article

Abstract: Obtaining the level of a factor that has the greatest effect on product development or crop cultivation is important given limited time, money, labor, and resources. Design of experiments is an approach to efficiently collect data in order to clarify the relationship between factors and effect. However, design of experiments mainly ends with the initial experimental design, which makes it difficult to conduct several more experiments based on the results. On the other hand, Bayesian Optimization, one of the methods of inverse estimation, uses Latin Hypercube design as the initial design of experiments and then conduct experiments sequentially. This is a powerful advantage of Bayesian Optimization.

Source: Total Quality Science

DOI: 10.17929/tqs.10.8

Authors: Shunya Furuuchi, Shu Yamada

Institution: Keio University

Language: English

Topic: Optimal Experimental Design Methods

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: diamond

Funder: Japan Society for the Promotion of Science

Award: Development and verification of process design method based on ICT platform for quality and efficiency in healthcare