Algorithms for clustering data
Algorithms for clustering data
Small Sample Size Effects in Statistical Pattern Recognition: Recommendations for Practitioners
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised texture segmentation using Gabor filters
Pattern Recognition
Estimating attributes: analysis and extensions of RELIEF
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Floating search methods in feature selection
Pattern Recognition Letters
Cluster-based text categorization: a comparison of category search strategies
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Divergence Based Feature Selection for Multimodal Class Densities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Selection: Evaluation, Application, and Small Sample Performance
IEEE Transactions on Pattern Analysis and Machine Intelligence
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
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
Automatic subspace clustering of high dimensional data for data mining applications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
A Robust Competitive Clustering Algorithm With Applications in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Computing Surveys (CSUR)
Feature selection in unsupervised learning via evolutionary search
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dimensionality Reduction in Unsupervised Learning of Conditional Gaussian Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Feature Selection Using Feature Similarity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Learning of Finite Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stochastic Complexity in Statistical Inquiry Theory
Stochastic Complexity in Statistical Inquiry Theory
MML clustering of multi-state, Poisson, vonMises circular and Gaussian distributions
Statistics and Computing
Input Feature Selection by Mutual Information Based on Parzen Window
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Subset Selection Using a Genetic Algorithm
IEEE Intelligent Systems
Unsupervised Feature Selection Applied to Content-Based Retrieval of Lung Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Repairing Faulty Mixture Models using Density Estimation
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Feature selection for high-dimensional genomic microarray data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Efficient Feature Selection in Conceptual Clustering
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Feature Subset Selection and Order Identification for Unsupervised Learning
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
X-means: Extending K-means with Efficient Estimation of the Number of Clusters
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Feature Weighting in k-Means Clustering
Machine Learning
Using machine learning to improve information access
Using machine learning to improve information access
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Dependency-based feature selection for clustering symbolic data
Intelligent Data Analysis
Conceptual clustering in information retrieval
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Clustering quality based feature selection method
Machine Graphics & Vision International Journal
Bayesian Feature and Model Selection for Gaussian Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
MIC'06 Proceedings of the 25th IASTED international conference on Modeling, indentification, and control
WBE'06 Proceedings of the 5th IASTED international conference on Web-based education
Feature selection in robust clustering based on Laplace mixture
Pattern Recognition Letters
MILES: Multiple-Instance Learning via Embedded Instance Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Subset Selection and Ranking for Data Dimensionality Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition
Using association patterns for discrete-valed data clustering
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Localized feature selection for clustering
Pattern Recognition Letters
Developing a feature weight self-adjustment mechanism for a K-means clustering algorithm
Computational Statistics & Data Analysis
Multinomial mixture model with feature selection for text clustering
Knowledge-Based Systems
Computational Intelligence and Security
A Graphical Model for Content Based Image Suggestion and Feature Selection
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
A new feature selection method for Gaussian mixture clustering
Pattern Recognition
A Statistical Approach for Binary Vectors Modeling and Clustering
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Variational Bayesian Approach for Long-Term Relevance Feedback
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Variable selection in model-based clustering: A general variable role modeling
Computational Statistics & Data Analysis
A scalable framework for discovering coherent co-clusters in noisy data
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
On multivariate binary data clustering and feature weighting
Computational Statistics & Data Analysis
A bacterial evolutionary algorithm for automatic data clustering
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A fast band selection method to increase image contrast for multispectral image segmentation
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Learning the number of Gaussian cusing hypothesis test
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Robust analysis of MRS brain tumour data using t-GTM
Neurocomputing
Active curve axis Gaussian mixture models
Pattern Recognition
Regularized data fusion improves image segmentation
Proceedings of the 29th DAGM conference on Pattern recognition
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Model-based subspace clustering of non-Gaussian data
Neurocomputing
An outlier-aware data clustering algorithm in mixture models
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
Unsupervised feature selection for multi-cluster data
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Document clustering via dirichlet process mixture model with feature selection
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning multiple nonredundant clusterings
ACM Transactions on Knowledge Discovery from Data (TKDD)
Evolutionary-rough feature selection for face recognition
Transactions on rough sets XII
The SEM statistical mixture model of segmentation algorithm of brain vessel image
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
A unifying criterion for unsupervised clustering and feature selection
Pattern Recognition
Adapt the mRMR criterion for unsupervised feature selection
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
Unsupervised feature selection for salient object detection
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
An entropy weighting mixture model for subspace clustering of high-dimensional data
Pattern Recognition Letters
Simultaneous model selection and feature selection via BYY harmony learning
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
Target segmentation in scenes with diverse background
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Simultaneous non-gaussian data clustering, feature selection and outliers rejection
PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
Eigenvector sensitive feature selection for spectral clustering
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Model-based multidimensional clustering of categorical data
Artificial Intelligence
Simultaneous model-based clustering and visualization in the Fisher discriminative subspace
Statistics and Computing
Model-Based estimation of word saliency in text
DS'06 Proceedings of the 9th international conference on Discovery Science
Assessment of an unsupervised feature selection method for generative topographic mapping
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Data clustering: a user’s dilemma
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Decision fusion based unsupervised texture image segmentation
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Finding uninformative features in binary data
IDEAL'05 Proceedings of the 6th international conference on Intelligent Data Engineering and Automated Learning
Immune multiobjective optimization algorithm for unsupervised feature selection
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
An evaluation of filter and wrapper methods for feature selection in categorical clustering
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
Expert Systems with Applications: An International Journal
Feature subset-wise mixture model-based clustering via local search algorithm
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
A robust approach for multivariate binary vectors clustering and feature selection
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
Time series relevance determination through a topology-constrained hidden markov model
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Unsupervised gene selection and clustering using simulated annealing
WILF'05 Proceedings of the 6th international conference on Fuzzy Logic and Applications
Unsupervised feature and model selection for generalized Dirichlet mixture models
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Journal of Visual Communication and Image Representation
Model-based clustering of high-dimensional data: Variable selection versus facet determination
International Journal of Approximate Reasoning
Simultaneous feature selection and clustering using particle swarm optimization
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part I
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
On online high-dimensional spherical data clustering and feature selection
Engineering Applications of Artificial Intelligence
Probability-based text clustering algorithm by alternately repeating two operations
Journal of Information Science
Journal of Information Science
Model-based clustering of high-dimensional data: A review
Computational Statistics & Data Analysis
A mixed integer linear model for clustering with variable selection
Computers and Operations Research
A survey on feature selection methods
Computers and Electrical Engineering
Fuzzy clustering with biological knowledge for gene selection
Applied Soft Computing
Semi-supervised projected model-based clustering
Data Mining and Knowledge Discovery
Hi-index | 0.15 |
Clustering is a common unsupervised learning technique used to discover group structure in a set of data. While there exist many algorithms for clustering, the important issue of feature selection, that is, what attributes of the data should be used by the clustering algorithms, is rarely touched upon. Feature selection for clustering is difficult because, unlike in supervised learning, there are no class labels for the data and, thus, no obvious criteria to guide the search. Another important problem in clustering is the determination of the number of clusters, which clearly impacts and is influenced by the feature selection issue. In this paper, we propose the concept of feature saliency and introduce an expectation-maximization (EM) algorithm to estimate it, in the context of mixture-based clustering. Due to the introduction of a minimum message length model selection criterion, the saliency of irrelevant features is driven toward zero, which corresponds to performing feature selection. The criterion and algorithm are then extended to simultaneously estimate the feature saliencies and the number of clusters.