SPOT (2.0.3)

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.

Maintainer: Martin Zaefferer
Author(s): 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]

License: GPL (>= 2)

Uses: DEoptim, MASS, nloptr, plotly, randomForest, rgenoud, rsm, testthat
Reverse depends: TDMR

Released almost 2 years ago.