O nekaterih lastnostih mnogorazsežnih podatkovij - Kastrin, Andrej (Informatica Medica Slovenica, 2023)
The extensive use of high-dimensional data to examine certain research phenomena has expanded in parallel with high-throughput technologies in various scientific fields. However, several statistical challenges arise when analysing high-dimensional datasets, such as low identifiability, numerical instability, and overfitting. Before delving into the complex analysis of high-dimensional data, a solid foundation of their inherent properties is crucial. This review aims to illustrate the geometric properties inherent in the statistical analysis of high-dimensional data by examining the behaviour of hypercubes and hyperspheres in a high-dimensional context. An overview of literature is also provided to guide the students in further study.
Keywords: high-dimensional data; machine learning; mnogorazsežni podatki; statistics; statistika; strojno učenje