Mutual Information Estimation

Mutual information estimation involves estimating the mutual information between two random variables from samples, particularly suitable for high-dimensional variables. This task aims to accurately quantify the dependence between variables through effective methods, providing crucial references for data mining, feature selection, and optimization of machine learning models. Supported by methodological approaches, mutual information estimation can handle complex data structures, revealing potential patterns of information interaction, and possesses extensive application value.