Rgtsp: a generalized top scoring pairs package for class prediction | Zendy

Vlad Popovici | Zendy; Eva Budínská | Zendy; Mauro Delorenzi | Zendy

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Rgtsp: a generalized top scoring pairs package for class prediction

Author(s) -

Vlad Popovici,

Eva Budínská,

Mauro Delorenzi

Publication year - 2011

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr233

Subject(s) - computer science , classifier (uml) , r package , source code , data mining , class (philosophy) , artificial intelligence , machine learning , pattern recognition (psychology) , programming language

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.

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