Benchmarking Classification Algorithms on High-Performance Computing Clusters
Benchmarking Classification Algorithms on High-Performance Computing Clusters
复制标题
高性能计算集群上的分类算法基准测试
DOI：
10.1007/978-3-319-01595-8_3
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发表时间：
2012
影响因子：
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通讯作者：
C. Weihs
中科院分区：
文献类型：
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作者：
B. Bischl;J. Schiffner;C. Weihs
分类算法的比较和基准测试是应用数据分析中的一个重要课题。这种广泛而彻底的研究将产生相当大的计算负担，因此最好将其委托给高性能计算集群。我们建立在我们最近开发的R包BatchJobs(集群函数式编程中的映射、缩减和过滤操作)和BatchExaments(统计实验的并行化和管理)的基础上。使用这两个包，这样的实验现在可以有效地和可重复性地进行，对研究人员来说，只需最少的努力。我们给出了标准分类算法的基准测试结果，并研究了预处理步骤对其性能的影响。
Comparing and benchmarking classification algorithms is an important topic in applied data analysis. Extensive and thorough studies of such a kind will produce a considerable computational burden and are therefore best delegated to high-performance computing clusters. We build upon our recently developed R packages BatchJobs (Map, Reduce and Filter operations from functional programming for clusters) and BatchExperiments (Parallelization and management of statistical experiments). Using these two packages, such experiments can now effectively and reproducibly be performed with minimal effort for the researcher. We present benchmarking results for standard classification algorithms and study the influence of pre-processing steps on their performance.