We develop a new multiclass classification method that reduces the multiclass problem to a single binary classifier (SBC). Our method constructs the binary problem by embedding sm...
Abstract. In this paper a novel framework for brain classification is proposed in the context of mental health research. A learning by example method is introduced by combining loc...
Umberto Castellani, E. Rossato, Vittorio Murino, M...
The authors previously proposed a self-organizing Hierarchical Cerebellar Model Articulation Controller (HCMAC) neural network containing a hierarchical GCMAC neural network and a ...
Experiments were conducted to test several hypotheses on methods for improving document classification for the malicious insider threat problem within the Intelligence Community. ...
We address feature selection problems for classification of small samples and high dimensionality. A practical example is microarray-based cancer classification problems, where sa...