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titleBayesian automatic relevance determination algorithms for classifying gene expression data
authorsYi Li, Colin Campbell, and Michael Tipping
abstractMotivation: We investigate two new Bayesian classification algorithms incorporating feature selection. These algorithms are applied to the classification of gene expression data derived from cDNA microarrays.

Results: We demonstrate the effectiveness of the algorithms on three gene expression datasets for cancer, showing they compare well with alternative kernel-based techniques. By automatically incorporating feature selection, accurate classifiers can be constructed utilizing very few features and with minimal hand-tuning. We argue that the feature selection is meaningful and some of the highlighted genes appear to be medically important.
typeJournal Paper
published year
(Total records:1429)
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