Simultaneous model selection and feature selection via BYY harmony learning

Authors:
Hongyan Wang;Jinwen Ma
Affiliations:
Department of Information Science, School of Mathematical Sciences & LMAM, Peking University, Beijing, P.R. China;Department of Information Science, School of Mathematical Sciences & LMAM, Peking University, Beijing, P.R. China
Venue:
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
Year:
2011

Citing 17
Cited 0

Small Sample Size Effects in Statistical Pattern Recognition: Recommendations for Practitioners

IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Selection: Evaluation, Application, and Small Sample Performance

IEEE Transactions on Pattern Analysis and Machine Intelligence
Selection of relevant features and examples in machine learning

Artificial Intelligence - Special issue on relevance
Wrappers for feature subset selection

Artificial Intelligence - Special issue on relevance
Unsupervised Learning of Finite Mixture Models

IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian model search for mixture models based on optimizing variational bounds

Neural Networks
Efficient Feature Selection in Conceptual Clustering

ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
BYY harmony learning, structural RPCL, and topological self-organizing on mixture models

Neural Networks - New developments in self-organizing maps
Feature Selection for Clustering - A Filter Solution

ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Simultaneous Feature Selection and Clustering Using Mixture Models

IEEE Transactions on Pattern Analysis and Machine Intelligence
BYY Harmony Learning on Finite Mixture: Adaptive Gradient Implementation and A Floating RPCL Mechanism

Neural Processing Letters
The BYY annealing learning algorithm for Gaussian mixture with automated model selection

Pattern Recognition
A fast fixed-point BYY harmony learning algorithm on Gaussian mixture with automated model selection

Pattern Recognition Letters
Simultaneous Localized Feature Selection and Model Detection for Gaussian Mixtures

IEEE Transactions on Pattern Analysis and Machine Intelligence
A filter feature selection method for clustering

ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
A cost-function approach to rival penalized competitive learning (RPCL)

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Unsupervised Learning of Gaussian Mixtures Based on Variational Component Splitting

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

Model selection for Gaussian mixture learning on a given dataset is an important but difficulty task and also depends on the feature or variable selection in practical applications. In this paper, we propose a new kind of learning algorithm for Gaussian mixtures with simultaneous model selection and variable selection (MSFS) based on the BYY harmony learning framework. It is demonstrated by simulation experiments that the proposed MSFS algorithm is able to solve the model selection and feature selection problems of Gaussian mixture learning on a given dataset simultaneously.