L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Creating courses by combining Learning Objects (LOs) sourced from third parties, known as courseware, is becoming more popular of late. Although courseware has advantages over tra...
Abstract. We compare three systems for the task of synthesising functional recursive programs, namely Adate, an approach through evolutionary computation, the classification learn...
Martin Hofmann 0008, Andreas Hirschberger, Emanuel...
SuperParent-One-Dependence Estimators (SPODEs) loosen Naive-Bayes’ attribute independence assumption by allowing each attribute to depend on a common single attribute (superpare...
Ying Yang, Kevin B. Korb, Kai Ming Ting, Geoffrey ...
Concept drifting in data streams often occurs unpredictably at any time. Currently many classification mining algorithms deal with this problem by using an incremental learning ap...