Elements of machine learning
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
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
Knowledge Acquisition Via Incremental Conceptual Clustering
Machine Learning
Determining Property Relevance in Concept Formation by Computing Correlation Between Properties
ECML '98 Proceedings of the 10th European Conference on 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
Dimensionality Reduction of Unsupervised Data
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Dimensionality Reduction in Unsupervised Learning of Conditional Gaussian Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic Feature Selection in Incremental Hierarchical Clustering
ECML '00 Proceedings of the 11th European Conference on Machine Learning
Subspace clustering for high dimensional data: a review
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Simultaneous Feature Selection and Clustering Using Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rearranging data objects for efficient and stable clustering
Proceedings of the 2005 ACM symposium on Applied computing
Hierarchical fuzzy filter method for unsupervised feature selection
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
An image content description technique for the inspection of specular objects
EURASIP Journal on Advances in Signal Processing
Learning from labeled and unlabeled data: an empirical study across techniques and domains
Journal of Artificial Intelligence Research
Feature selection for genomic data sets through feature clustering
International Journal of Data Mining and Bioinformatics
Journal of Network and Computer Applications
A clustering based system for instant detection of cardiac abnormalities from compressed ECG
Expert Systems with Applications: An International Journal
Similarity-margin based feature selection for symbolic interval data
Pattern Recognition Letters
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
Feature selection using structural similarity
Information Sciences: an International Journal
Feature selection with SVD entropy: Some modification and extension
Information Sciences: an International Journal
| Hi-index | 0.00 |
Feature selection is a central problem in data analysis that have received a significant amount of attention from several disciplines, such as machine learning or pattern recognition. However, most of the research has been addressed towards supervised tasks, paying little attention to unsupervised learning. In this paper, we introduce an unsupervised feature selection method for symbolic clustering tasks. Our method is based upon the assumption that, in the absence of class labels, we can deem as irrelevant those features that exhibit low dependencies with the rest of features. Experiments with several data sets demonstrate that the proposed approach is able to detect completely irrelevant features and that, additionally, it removes other features without significantly hurting the performance of the clustering algorithm.