Application of Small Sample Information Processing in High Dimensional Space
Shanshan Yuan · 2021
Often times it is difficult to collect sufficient large dataset to support the test or validation of given hypotheses. Information diffusion is an effective way to mitigate the issue. Research results have been reported on information diffusion in one-dimensional space and two-dimensional Euclidean space. This paper attempts to extend the research to three-dimensional space. The main idea is to decompose a three-dimensional problem to two-dimensional problems using the golden section rule. A case study on a real-world small dataset analysis is provided to demonstrate the effectiveness of the proposed approach.