This work is an initial exploration of the use of the decision-theoretic concept of utility to guide pattern mining. We … formulate several pattern mining problems that use utility functions. Utility guided pattern mining provides the twin benefits … utility guided pattern mining problem. It addresses the drawbacks of threshold guided pattern mining, the specification of …

approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety … intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify …. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set …

collected at the scene. Outcomes were measured during a three month follow-up. The data were analyzed with modern data mining …

discovery and data mining modeling problems. In this dissertation work, a framework named Granular Support Vector Machines (GSVM …) is proposed to systematically and formally combine statistical learning theory, granular computing theory and soft … computing theory to address challenging predictive data modeling problems effectively and/or efficiently, with specific focus on …

al, 2010). Literature indicates that data mining or algorithmic approaches to prediction can provide superior results vis … 2009). However, little research in higher education has focused on the employment of data mining methods for predicting …