Package: OOR 0.1.4

OOR: Optimistic Optimization in R

Implementation of optimistic optimization methods for global optimization of deterministic or stochastic functions. The algorithms feature guarantees of the convergence to a global optimum. They require minimal assumptions on the (only local) smoothness, where the smoothness parameter does not need to be known. They are expected to be useful for the most difficult functions when we have no information on smoothness and the gradients are unknown or do not exist. Due to the weak assumptions, however, they can be mostly effective only in small dimensions, for example, for hyperparameter tuning.

Authors:M. Binois [cre, aut, trl], A. Carpentier [aut], J.-B. Grill [aut], R. Munos [aut], M. Valko [aut, ctb]

OOR_0.1.4.tar.gz
OOR_0.1.4.zip(r-4.7-any)OOR_0.1.4.zip(r-4.6-any)OOR_0.1.4.zip(r-4.5-any)
OOR_0.1.4.tgz(r-4.6-any)OOR_0.1.4.tgz(r-4.5-any)
OOR_0.1.4.tar.gz(r-4.7-any)OOR_0.1.4.tar.gz(r-4.6-any)
OOR_0.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
OOR/json (API)

# Install 'OOR' in R:
install.packages('OOR', repos = c('https://mbinois.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mbinois/oor/issues

On CRAN:

Conda:

3.80 score 2 packages 21 scripts 339 downloads 8 exports 0 dependencies

Last updated from:5517a187de. Checks:7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develWARNING89
source / vignettesOK148
linux-releaseWARNING82
macos-releaseWARNING87
macos-oldrelWARNING72
windows-develWARNING44
windows-releaseWARNING50
windows-oldrelWARNING65
wasm-releaseOK71

Exports:difficultdifficult2double_sineguirlandplotStoSOOPOOsin1StoSOO

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
Package OOROOR-package OOR
Parallel Optimistic OptimizationPOO
StoSOO and SOO algorithmsStoSOO
Test functions of 'x'difficult difficult2 double_sine guirland sin1 Test functions