Ioannis A. Sarafis

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In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data Mining (DM) clustering applications. NOCEA evolves individuals that consist of a variable number of non-overlapping clustering rules, where each rule includes d intervals, one for each feature. The encoding scheme is non-binary as the values for the boundaries(More)
Clustering is a descriptive data mining task aiming to group the data into homogeneous groups. This paper presents a novel evolutionary algorithm (NOCEA) that efficiently and effectively clusters massive numerical databases. NOCEA evolves individuals of variable-length consisting of disjoint and axis-aligned hyper-rectangular rules with homogeneous data(More)
Carotid atherosclerosis is the main cause of fatal cerebral ischemic events, thereby posing a major burden for public health and state economies. We propose a web-based platform named CAROTID to address the need for optimal management of patients with carotid atherosclerosis in a twofold sense: (a) objective selection of patients who need(More)
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