Approximating mutual information by maximum likelihood density ratio estimation
Mutual information is useful in various data processing tasks such as feature selection or
independent component analysis. In this paper, we propose a new method of approximating …
independent component analysis. In this paper, we propose a new method of approximating …
A comparison of multivariate mutual information estimators for feature selection
G Doquire, M Verleysen - International Conference on Pattern …, 2012 - scitepress.org
Mutual Information estimation is an important task for many data mining and machine
learning applications. In particular, many feature selection algorithms make use of the …
learning applications. In particular, many feature selection algorithms make use of the …
A constructive density-ratio approach to mutual information estimation: experiments in feature selection
I Braga - Journal of Information and Data Management, 2014 - periodicos.ufmg.br
Mutual Information (MI) estimation is an important component of several data mining tasks
(eg feature selection). In classification settings, MI estimation essentially depends on the …
(eg feature selection). In classification settings, MI estimation essentially depends on the …
On estimating mutual information for feature selection
E Schaffernicht, R Kaltenhaeuser, SS Verma… - … Conference on Artificial …, 2010 - Springer
Mutual Information (MI) is a powerful concept from information theory used in many
application fields. For practical tasks it is often necessary to estimate the Mutual Information …
application fields. For practical tasks it is often necessary to estimate the Mutual Information …
Computationally efficient estimation of squared-loss mutual information with multiplicative kernel models
T Sakai, M Sugiyama - IEICE TRANSACTIONS on Information and …, 2014 - search.ieice.org
Squared-loss mutual information (SMI) is a robust measure of the statistical dependence
between random variables. The sample-based SMI approximator called least-squares …
between random variables. The sample-based SMI approximator called least-squares …
Critical values of a kernel density-based mutual information estimator
Recently, mutual information (MI) has become widely recognized as a statistical measure of
dependence that is suitable for applications where data are non-Gaussian, or where the …
dependence that is suitable for applications where data are non-Gaussian, or where the …
Mutual information for feature selection: estimation or counting?
In classification, feature selection is an important pre-processing step to simplify the dataset
and improve the data representation quality, which makes classifiers become better, easier …
and improve the data representation quality, which makes classifiers become better, easier …
A mutual information estimator for continuous and discrete variables applied to feature selection and classification problems
Abstract Currently Mutual Information has been widely used in pattern recognition and
feature selection problems. It may be used as a measure of redundancy between features as …
feature selection problems. It may be used as a measure of redundancy between features as …
Quadratic mutual information feature selection
D Sluga, U Lotrič - Entropy, 2017 - mdpi.com
We propose a novel feature selection method based on quadratic mutual information which
has its roots in Cauchy–Schwarz divergence and Renyi entropy. The method uses the direct …
has its roots in Cauchy–Schwarz divergence and Renyi entropy. The method uses the direct …