BatchJobs and BatchExperiments: Abstraction Mechanisms for Using R in Batch Environments
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DOI: http://hdl.handle.net/10.18637/jss.v064.i11
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References listed on IDEAS
- Kane, Michael & Emerson, John W. & Weston, Stephen, 2013. "Scalable Strategies for Computing with Massive Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 55(i14).
- Hoffmann, Thomas J., 2011. "Passing in Command Line Arguments and Parallel Cluster/Multicore Batching in R with batch," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 39(c01).
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Cited by:
- Daniel Horn & Aydın Demircioğlu & Bernd Bischl & Tobias Glasmachers & Claus Weihs, 2018. "A comparative study on large scale kernelized support vector machines," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(4), pages 867-883, December.
- Wright, Marvin N. & Ziegler, Andreas, 2017. "ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i01).
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