Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...
Associative classification is a promising classification approach that utilises association rule mining to construct accurate classification models. In this paper, we investigate ...
The information explosion in today’s electronic world has created the need for information filtering techniques that help users filter out extraneous content to identify the righ...
Kannan Chandrasekaran, Susan Gauch, Praveen Lakkar...
The management of large databases of hierarchical (e.g., multi-scale or multilevel) image features is a common problem in object recognition. Such structures are often represented ...
Abstract. The aim of this work is to forecast future events in financial data sets, in particular, we focus our attention on situations where positive instances are rare, which fal...