A method for extracting nonlinear structure based on measures of dependence

DOI10.1007/s42081-022-00177-9zbMath1502.62069OpenAlexW4294018375MaRDI QIDQ2103283

Hiroyuki Minami, Masahiro Mizuta, Shoma Ishimoto

Publication date: 13 December 2022

Published in: Japanese Journal of Statistics and Data Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s42081-022-00177-9

zbMATH Keywords

projection pursuitTICMIC

Mathematics Subject Classification ID

Measures of association (correlation, canonical correlation, etc.) (62H20)

Cites Work

• Unnamed Item
• Measuring and testing dependence by correlation of distances
• Detecting Novel Associations in Large Data Sets
• An empirical study of the maximal and total information coefficients and leading measures of dependence
• Multiplier and gradient methods
• Measuring dependence powerfully and equitably
• Exploratory Projection Pursuit
• Algorithmic Learning Theory
• A Non-Parametric Test of Independence