benchmark

datasets

Sampling function, see <code><a href="/link/benchmark-sampling?package=benchmark&version=0.3-3" rd-options="" 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 href="/link/predict?package=benchmark&version=0.3-3&to=stats" rd-options="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 href="/link/benchmark-comptime?package=benchmark&version=0.3-3" rd-options="" data-mini-rdoc="benchmark::benchmark-comptime">benchmark-comptime</a></code>.

performances

<code><a href="/link/DatasetCharacteristics?package=benchmark&version=0.3-3" rd-options="" data-mini-rdoc="benchmark::DatasetCharacteristics">DatasetCharacteristics</a></code> object

characteristics

<code><a href="/link/TestProcedure?package=benchmark&version=0.3-3" rd-options="" data-mini-rdoc="benchmark::TestProcedure">TestProcedure</a></code> object

test

test.burnin

verbose

Function to execute benchmark experiments and 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 execution

Description

Usage

Arguments

Value

See Also