Information Processing Letters
Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Applied multivariate statistical analysis
Applied multivariate statistical analysis
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
A near-optimal initial seed value selection in K-means algorithm using a genetic algorithm
Pattern Recognition Letters
Bayesian classification (AutoClass): theory and results
Advances in knowledge discovery and data mining
From complex environments to complex behaviors
Adaptive Behavior - Special issue on environment structure and behavior
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
CURE: an efficient clustering algorithm for large databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
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
The handbook of brain theory and neural networks
Feature selection for ensembles
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Visualization and interactive feature selection for unsupervised data
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Feature selection in unsupervised learning via evolutionary search
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Clustering Algorithms
Statistical Themes and Lessons for Data Mining
Data Mining and Knowledge Discovery
BIRCH: A New Data Clustering Algorithm and Its Applications
Data Mining and Knowledge Discovery
Feature Subset Selection Using a Genetic Algorithm
IEEE Intelligent Systems
Knowledge Acquisition Via Incremental Conceptual Clustering
Machine Learning
Efficient Feature Selection in Conceptual Clustering
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Feature Selection as a Preprocessing Step for Hierarchical Clustering
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Model Selection in Unsupervised Learning with Applications To Document Clustering
ICML '99 Proceedings of the Sixteenth 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
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Feature Selection Via Mathematical Programming
INFORMS Journal on Computing
Introduction to the Special Issue: Multicriterion Optimization
Evolutionary Computation
Efficient and Scalable Pareto Optimization by Evolutionary Local Selection Algorithms
Evolutionary Computation
Clustering with a genetically optimized approach
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Feature Selection for Unsupervised Learning
The Journal of Machine Learning Research
A Dual-Objective Evolutionary Algorithm for Rules Extraction in Data Mining
Computational Optimization and Applications
Information preserving multi-objective feature selection for unsupervised learning
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Multiobjective Optimization in Bioinformatics and Computational Biology
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Unsupervised feature weighting with multi niche crowding genetic algorithms
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Mixture-model cluster analysis using information theoretical criteria
Intelligent Data Analysis
Clustering stability-based feature selection for unsupervised texture classification
Machine Graphics & Vision International Journal
Feature selection for genomic data sets through feature clustering
International Journal of Data Mining and Bioinformatics
Using biclustering for automatic attribute selection to enhance global visualization
VIEW'06 Proceedings of the 1st first visual information expert conference on Pixelization paradigm
Combining evolutionary and sequential search strategies for unsupervised feature selection
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
A unifying criterion for unsupervised clustering and feature selection
Pattern Recognition
Nearest-neighbor guided evaluation of data reliability and its applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
International Journal of Bio-Inspired Computation
Exploiting the trade-off — the benefits of multiple objectives in data clustering
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Visual interactive evolutionary algorithm for high dimensional data clustering and outlier detection
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
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
Multiobjective optimization of co-clustering ensembles
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
An evolutionary approach for high dimensional attribute selection
International Journal of Intelligent Information and Database Systems
Unsupervised fuzzy-rough set-based dimensionality reduction
Information Sciences: an International Journal
Automatic feature selection for named entity recognition using genetic algorithm
Proceedings of the Fourth Symposium on Information and Communication Technology
International Journal of Hybrid Intelligent Systems
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Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and possibly, accuracy of the resulting models. Feature selection has traditionally been studied in supervised learning situations, with some estimate of accuracy used to evaluate candidate subsets. However, we often cannot apply supervised learning for lack of a training signal. For these cases, we propose a new feature selection approach based on clustering. A number of heuristic criteria can be used to estimate the quality of clusters built from a given feature subset. Rather than combining such criteria, we use ELSA, an evolutionary local selection algorithm that maintains a diverse population of solutions that approximate the Pareto front in a multi-dimensional objective space. Each evolved solution represents a feature subset and a number of clusters; two representative clustering algorithms, K-means and EM, are applied to form the given number of clusters based on the selected features. Experimental results on both real and synthetic data show that the method can consistently find approximate Pareto-optimal solutions through which we can identify the significant features and an appropriate number of clusters. This results in models with better and clearer semantic relevance.