Laura Maria Cannas

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Evolutionary algorithms have received much attention in extracting knowledge on high-dimensional micro-array data, being crucial to their success a suitable definition of the search space of the potential solutions. In this paper, we present an evolutionary approach for selecting informative genes (features) to predict and diagnose cancer. We propose a(More)
Methods currently used for micro-array data classification aim to select a minimum subset of features, namely a predictor, that is necessary to construct a classifier of best accuracy. Although effective, they lack in facing the primary goal of domain experts that are interested in detecting different groups of biologically relevant markers. In this paper,(More)
No part of this journal may be reproduced or used in any form or by any means without written permission from the publisher, except for noncommercial, educational use including classroom teaching purposes. Product or company names used in this journal are for identification purposes only. Inclusion of the names of the products or companies does not indicate(More)
In the last ten years, automatic Text Categorization (TC) has been gaining an increasing interest from the research community, due to the need to organize a massive number of digital documents. Following a machine learning paradigm, this paper presents a model which regards TC as a classification task supported by a wrapper approach and combines the(More)
The lymphatic system, consisting of the lymph nodes and the lymphatic vessels as well as the spleen and various sites of lymphoid tissue, is deputed to important tasks: the immune response, the transport of lipids absorbed at the intestinal level and the reabsorption of water and other substances from the interstitial spaces; the lymph nodes in particular(More)
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