SPOT: Sequential Parameter Optimization Toolbox

A set of tools for model based optimization and tuning of algorithms. It includes surrogate models, optimizers and design of experiment approaches. The main interface is spot, which uses sequentially updated surrogate models for the purpose of efficient optimization. The main goal is to ease the burden of objective function evaluations, when a single evaluation requires a significant amount of resources.

Version: 2.0.3
Depends: R (≥ 3.0.0)
Imports: randomForest, stats, utils, graphics, grDevices, MASS, DEoptim, rgenoud, plotly, rsm, nloptr
Suggests: testthat
Published: 2018-05-14
Author: Thomas Bartz-Beielstein [aut], Joerg Stork [aut], Martin Zaefferer [aut, cre], Margarita Rebolledo [ctb], Christian Lasarczyk [ctb], Joerg Ziegenhirt [ctb], Wolfgang Konen [ctb], Oliver Flasch [ctb], Patrick Koch [ctb], Martina Friese [ctb], Lorenzo Gentile [ctb], Frederik Rehbach [ctb]
Maintainer: Martin Zaefferer <martin.zaefferer at gmx.de>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: SPOT citation info
Materials: NEWS
CRAN checks: SPOT results

Downloads:

Reference manual: SPOT.pdf
Package source: SPOT_2.0.3.tar.gz
Windows binaries: r-devel: SPOT_2.0.3.zip, r-release: SPOT_2.0.3.zip, r-oldrel: SPOT_2.0.3.zip
OS X binaries: r-release: SPOT_2.0.3.tgz, r-oldrel: SPOT_2.0.3.tgz
Old sources: SPOT archive

Reverse dependencies:

Reverse depends: TDMR
Reverse imports: spotGUI

Linking:

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