Marilena Pillati

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Some real problems, such as image recognition or the analysis of gene expression data, involve the observation of a very large number of variables on a few units. In such a context conventional classification methods are difficult to employ both from analytical and interpretative points of view. In this paper, a solution based on locally linear embedding(More)
The analysis of gene expression data involves the observation of a very large number of variables (genes) on a few units (tissues). In such a context the recourse to conventional classification methods may be hard both for analytical and interpretative reasons. In this work a gene selection procedure for classification problems is addressed. The(More)
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