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 paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Developing models and methods to manage data vagueness is a current effervescent research field. Some work has been done with supervised problems but unsupervised problems and unce...
BAYDA is a software package for flexible data analysis in predictive data mining tasks. The mathematical model underlying the program is based on a simple Bayesian network, the Na...
In many computer vision tasks like face recognition and image retrieval, one is often confronted with high-dimensional data. Procedures that are analytically or computationally ma...