Clustering is inherently a difficult task and is made even more difficult when the selection of relevant features is also an issue. In this paper, we propose an approach for simult...
Iterative search margin based algorithm(Simba) has been proven effective for feature selection. However, it still has the following disadvantages: (1) the previously proposed model...
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
In this work, we suggest a new feature selection technique that lets us use the wrapper approach for finding a well suited feature set for distinguishing experiment classes in hig...
Abstract. We deal with two important problems in pattern recognition that arise in the analysis of large datasets. While most feature subset selection methods use statistical techn...