Title :
Multivariate Edgeworth-Based Entropy Estimation
Author :
Van Hulle, Marc M.
Author_Institution :
K.U. Leuven
Abstract :
We develop the general, multivariate case of the Edgeworth approximation of differential entropy, and introduce an approximate formula for Gaussian mixture densities. We use these entropy approximations in a new algorithm for selecting the optimal number of clusters in a data set, and in a new mutual information test with which one can statistically decide whether a distribution can be factorized along a given set of axes
Keywords :
Gaussian processes; entropy; estimation theory; Edgeworth approximation; Gaussian mixture density; data clusters; differential entropy; multivariate Edgeworth-based entropy estimation; Clustering algorithms; Educational programs; Electronic mail; Entropy; Independent component analysis; Laboratories; Mutual information; Polynomials; Psychology; Testing;
Conference_Titel :
Machine Learning for Signal Processing, 2005 IEEE Workshop on
Conference_Location :
Mystic, CT
Print_ISBN :
0-7803-9517-4
DOI :
10.1109/MLSP.2005.1532920
