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 Feature Selection Using Feature Similarity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Unsupervised Feature Selection Applied to Content-Based Retrieval of Lung Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cluster validation techniques for genome expression data
Signal Processing - Special issue: Genomic signal processing
Simultaneous Feature Selection and Clustering Using Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
The discriminating power of random features
Proceedings of the 2009 conference on Neural Nets WIRN09: Proceedings of the 19th Italian Workshop on Neural Nets, Vietri sul Mare, Salerno, Italy, May 28--30 2009
Enhanced feature selection algorithm using Ant Colony Optimization and fuzzy memberships
BioMED '08 Proceedings of the Sixth IASTED International Conference on Biomedical Engineering
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When applied to genomic data, many popular unsupervised explorative data analysis tools based on clustering algorithms often fail due to their small cardinality and high dimensionality. In this paper we propose a wrapper method for gene selection based on simulated annealing and unsupervised clustering. The proposed approach, even if computationally intensive, permits to select the most relevant features (genes), and to rank their relevance, allowing to improve the results of clustering algorithms.