—Lack of supervision in clustering algorithms often leads to clusters that are not useful or interesting to human reviewers. We investigate if supervision can be automatically tr...
— We present a solution to the problem of identifying clusters from MIMO measurement data in a data window, with a minimum of user interaction. Conventionally, visual inspection ...
Nicolai Czink, Pierluigi Cera, Jari Salo, Ernst Bo...
Genetic Programming offers freedom in the definition of the cost function that is unparalleled among supervised learning algorithms. However, this freedom goes largely unexploited...
Background: This paper presents a unified framework for finding differentially expressed genes (DEGs) from the microarray data. The proposed framework has three interrelated modul...
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...