Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
A distributed data mining algorithm to improve the detection accuracy when classifying malicious or unauthorized network activity is presented. The algorithm is based on genetic p...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Clustering ensembles has been recently recognized as an emerging approach to provide more robust solutions to the data clustering problem. Current methods of clustering ensembles ...
The advent of real-time fMRI pattern classification opens many avenues for interactive self-regulation where the brain's response is better modelled by multivariate, rather t...
Catrin Oliver Plumpton, Ludmila I. Kuncheva, David...