GetClusteringExampleMicrobenchmarks

<code>GetClusteringExampleMicrobenchmarks</code> defines the example clustering
microbenchmarks to be executed by the
<code><a rd-options="" href="/link/RunMachineLearningBenchmark?package=RHPCBenchmark&version=0.1.0" data-mini-rdoc="RHPCBenchmark::RunMachineLearningBenchmark">RunMachineLearningBenchmark</a></code> function.  The example
are chosen so that they can run in a few minutes or less.
<ol>
<li>pam_cluster_3_7_2500N=3, seven clusters with 2500 vectors per
     cluster
   </li>
<li>clara_cluster_64_33_1213N=64, 33 clusters with 1213 vectors per
     cluster
</li>
</ol><p></p><p>See the documentation for the
<code><a rd-options="" href="/link/ClusteringMicrobenchmark?package=RHPCBenchmark&version=0.1.0" data-mini-rdoc="RHPCBenchmark::ClusteringMicrobenchmark">ClusteringMicrobenchmark</a></code> class for more details.</p>

Microbenchmarks for determining the run time
performance of aspects of the R programming environment and packages
relevant to high-performance computation.  The benchmarks are divided into
three categories: dense matrix linear algebra kernels, sparse matrix linear
algebra kernels, and machine learning functionality.

James McCombs

GetClusteringExampleMicrobenchmarks: Initializes the list of example clustering microbenchmarks

Description

Usage

Arguments

Value

See Also