This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Handing unbalanced data and noise are two important issues in the field of machine learning. This paper proposed a complete framework of fuzzy relevance vector machine by weightin...
Abstract--In this paper we investigate the sparsity and recognition capabilities of two approximate Bayesian classification algorithms, the multi-class multi-kernel Relevance Vecto...
Ioannis Psorakis, Theodoros Damoulas, Mark A. Giro...
Students’ actions while working with a tuoring system were used to generate estimates of learning goals, specifically, the goal of learning by using multimedia help resources, an...
Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a mode...