Recently, there has been tremendous interest in developing graph-based subspace
clustering in high-dimensional data, which does not require a priori knowledge of the …

Biomedical datasets distill many mechanisms of human diseases, linking diseases to genes
and phenotypes (signs and symptoms of disease), genetic mutations to altered protein …

In general, a similarity threshold (ie, a vigilance parameter) for a node learning process in
Adaptive Resonance Theory (ART)-based algorithms has a significant impact on clustering …

Context recognition for lifelong learning (L2) agents is an open-ended problem whereby
aggregate features in an environment are utilized to signal the active context in which the …

This study details the biclustering methods for gene expression data, focusing on the
refinement of quality criteria essential for evaluating the generated bicluster structures. An …

У статті запропоновано новий підхід до аналізу даних за допомогою бікластерного
аналізу, який суттєво відрізняється від традиційної кластеризації. Автори …