Abstract
A top scoring pair (TSP) classifier consists of a pair of variables whose relative ordering can be used for accurately predicting the class label of a sample. This classification rule has the advantage of being easily interpretable and more robust against technical variations in data, as those due to different microarray platforms. Here we describe a parallel implementation of this classifier which significantly reduces the training time, and a number of extensions, including a multi-class approach, which has the potential of improving the classification performance. © The Author 2011. Published by Oxford University Press. All rights reserved.
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CITATION STYLE
Popovici, V., Budinská, E., & Delorenzi, M. (2011). Rgtsp: A generalized top scoring pairs package for class prediction. Bioinformatics, 27(12), 1729–1730. https://doi.org/10.1093/bioinformatics/btr233
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