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Microarray design using the Hilbert-schmidt independence criterion

Bedo, Justin


This paper explores the design problem of selecting a small subset of clones from a large pool for creation of a microarray plate. A new kernel based unsupervised feature selection method using the Hilbert-Schmidt independence criterion (hsic) is presented and evaluated on three microarray datasets: the Alon colon cancer dataset, the van 't Veer breast cancer dataset, and a multiclass cancer of unknown primary dataset. The experiments show that subsets selected by the hsic resulted in...[Show more]

CollectionsANU Research Publications
Date published: 2008
Type: Book chapter
DOI: 10.1007/978-3-540-88436-1_25


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