Abstract. Principal component analysis (PCA) and its dual—principal coordinate analysis (PCO)—are widely applied to unsupervised dimensionality reduction. In this paper, we sho...
Background: Two problems complicate the study of selection in viral genomes: Firstly, the presence of genes in overlapping reading frames implies that selection in one reading fra...
Saskia de Groot, Thomas Mailund, Gerton Lunter, Jo...
Background: Several algorithms have been proposed for detecting fluorescently labeled subcellular objects in microscope images. Many of these algorithms have been designed for spe...
: Bagging (Bootstrap Aggregating) has been proved to be a useful, effective and simple ensemble learning methodology. In generic bagging methods, all the classifiers which are trai...
This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...