A popular approach for dimensionality reduction and data analysis is principal component analysis (PCA). A limiting factor with PCA is that it does not inform us on which of the o...
Mahdokht Masaeli, Yan Yan, Ying Cui, Glenn Fung, J...
Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more effective and efficient. Many different feature sel...
The interplay between the mutation operator and the selection mechanism plays a fundamental role in the behaviour of evolutionary algorithms (EAs). However, this interplay is stil...
ACT We consider the problem of sensor selection in resource constrained sensor networks. The fusion center selects a subset of k sensors from an available pool of m sensors accordi...
Manohar Shamaiah, Siddhartha Banerjee, Haris Vikal...
Abstract. In many classification problems, and in particular in medical domains, it is common to have an unbalanced class distribution. This pose problems to classifiers as they ...