—Methods for learning decision rules are being successfully applied to many problem domains, especially where understanding and interpretation of the learned model is necessary. ...
Artificial neural networks have proven to be a successful, general method for inductive learning from examples. However, they have not often been viewed in terms of constructive ...
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
—This paper introduces new metrics for course evaluation. It is also proposes a ranking algorithm that classifies courses based on the previous course evaluation metrics and sugg...
Stavros Valsamidis, Ioannis Kazanidis, Sotirios Ko...
This paper proposes an efficient method to learn from multi source data with an Inductive Logic Programming method. The method is based on two steps. The first one consists in lea...