benchmark

datasets

Sampling function, see
  <code><a rd-options="" href="/link/benchmark-sampling?package=benchmark&version=0.3-6" data-mini-rdoc="benchmark::benchmark-sampling">benchmark-sampling</a></code>.

sampling

List of algorithms; i.e., functions
  which take a model formula and a data.frame to fit a
  model. Note that a <code><a rd-options="stats" href="/link/predict?package=benchmark&version=0.3-6&to=stats" data-mini-rdoc="stats::predict">predict</a></code> function
  must be defined as well.

algorithms

List of performance measure
  functions; i.e., functions with arguments <code>yhat</code> and
  <code>y</code>. See, e.g., <code><a rd-options="" href="/link/benchmark-comptime?package=benchmark&version=0.3-6" data-mini-rdoc="benchmark::benchmark-comptime">benchmark-comptime</a></code>.

performances

<code>DatasetCharacteristics</code>
  object; e.g., <code><a rd-options="" href="/link/StatlogCharacteristics?package=benchmark&version=0.3-6" data-mini-rdoc="benchmark::StatlogCharacteristics">StatlogCharacteristics</a></code>

characteristics

<code><a rd-options="" href="/link/TestProcedure?package=benchmark&version=0.3-6" data-mini-rdoc="benchmark::TestProcedure">TestProcedure</a></code> object

test

test.burnin

verbose


Function to execute benchmark experiments and to collect
all data the package can analyze. For more sophisticated
benchmark experiments we suggest the usage of the
<code>mlr</code> package.


The benchmark package provides a toolbox for setup, execution
and analysis of benchmark experiments. Main focus is the analysis of
data accumulating during the execution -- one primary objective is the
statistical correct computation of the candidate algorithms' order.

benchmark: Benchmark experiment setup and execution

Description

Usage

Arguments

Value

See Also