Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
In this paper we deal with the problem of feature selection by introducing a new approach based on Gravitational Search Algorithm (GSA). The proposed algorithm combines the optimi...
A relevance filter is proposed which removes features based on the mutual information between class labels and features. It is proven that both feature independence and class condi...
This paper introduces the Dynamic Mesh Optimization meta-heuristic, which falls under the evolutionary computation techniques. Moreover, we outline its application to the feature s...