A parallel random forest classifier for R

Lawrence Mitchell; Terence Sloan; Muriel Mewissen; Peter Ghazal; Thorsten Forster; Michal Piotrowski; Arthur S. Trew

doi:10.1145/1996023.1996024

A parallel random forest classifier for R

Lawrence Mitchell, Terence Sloan, Muriel Mewissen, Peter Ghazal, Thorsten Forster, Michal Piotrowski, Arthur S. Trew

Research output: Contribution to conference › Paper › peer-review

Abstract

The statistical language R is favoured by many biostaticians for processing microarray data. In recent times, the quantity of data that can be obtained in experiments has risen significantly, making previously fast analyses time consuming, or even not possible at all with the existing software infrastructure. High Performance Computing (HPC) systems offer a solution to these problems, but at the expense of increased complexity for the end user. The Simple Parallel R Interface (SPRINT) is a library for R that aims to reduce the complexity of using HPC systems by providing biostatisticians with drop-in parallelized replacements of existing R functions. In this paper we describe the implementation of a parallel version of the Random Forest classifier in the SPRINT library.

Original language	English
Pages	1-6
Number of pages	7
DOIs	https://doi.org/10.1145/1996023.1996024
Publication status	Published - 1 Jan 2011
Event	second international workshop on Emerging computational methods for the life sciences - San Jose, United States Duration: 8 Jun 2011 → …

Conference

Conference	second international workshop on Emerging computational methods for the life sciences
Country/Territory	United States
City	San Jose
Period	8/06/11 → …

Access to Document

10.1145/1996023.1996024

http://portal.acm.org/citation.cfm?doid=1996023.1996024

Cite this

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abstract = "The statistical language R is favoured by many biostaticians for processing microarray data. In recent times, the quantity of data that can be obtained in experiments has risen significantly, making previously fast analyses time consuming, or even not possible at all with the existing software infrastructure. High Performance Computing (HPC) systems offer a solution to these problems, but at the expense of increased complexity for the end user. The Simple Parallel R Interface (SPRINT) is a library for R that aims to reduce the complexity of using HPC systems by providing biostatisticians with drop-in parallelized replacements of existing R functions. In this paper we describe the implementation of a parallel version of the Random Forest classifier in the SPRINT library.",

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AU - Sloan, Terence

AU - Mewissen, Muriel

AU - Ghazal, Peter

AU - Forster, Thorsten

AU - Piotrowski, Michal

AU - Trew, Arthur S.

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ER -

A parallel random forest classifier for R

Abstract

Conference

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Fingerprint

SPRINTing further with HECToR

HPC Enabling of R Application Software

Cite this

A parallel random forest classifier for R

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Projects

SPRINTing further with HECToR

HPC Enabling of R Application Software

Cite this