DocumentCode
2415065
Title
Multivariate Edgeworth-Based Entropy Estimation
Author
Van Hulle, Marc M.
Author_Institution
K.U. Leuven
fYear
2005
fDate
28-28 Sept. 2005
Firstpage
311
Lastpage
316
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning for Signal Processing, 2005 IEEE Workshop on
Conference_Location
Mystic, CT
Print_ISBN
0-7803-9517-4
Type
conf
DOI
10.1109/MLSP.2005.1532920
Filename
1532920
Link To Document