Feature set partitioning generalizes the task of feature selection by partitioning the feature set into subsets of features that are collectively useful, rather than by finding a ...
This paper introduces two new algorithms to reduce the number of objectives in a multiobjective problem by identifying the most conflicting objectives. The proposed algorithms ar...
In this paper, we argue that for a C-class classification problem, C 2-class classifiers, each of which discriminating one class from the other classes and having a characteristic ...
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Abstract. In the artificial neural networks (ANNs), feature selection is a wellresearched problem, which can improve the network performance and speed up the training of the networ...