Package: finetune 1.3.0.9000

Max Kuhn

finetune: Additional Functions for Model Tuning

The ability to tune models is important. 'finetune' enhances the 'tune' package by providing more specialized methods for finding reasonable values of model tuning parameters. Two racing methods described by Kuhn (2014) <doi:10.48550/arXiv.1405.6974> are included. An iterative search method using generalized simulated annealing (Bohachevsky, Johnson and Stein, 1986) <doi:10.1080/00401706.1986.10488128> is also included.

Authors:Max Kuhn [aut, cre], Posit Software, PBC [cph, fnd]

finetune_1.3.0.9000.tar.gz
finetune_1.3.0.9000.zip(r-4.7)finetune_1.3.0.9000.zip(r-4.6)finetune_1.3.0.9000.zip(r-4.5)
finetune_1.3.0.9000.tgz(r-4.6-any)finetune_1.3.0.9000.tgz(r-4.5-any)
finetune_1.3.0.9000.tar.gz(r-4.7-any)finetune_1.3.0.9000.tar.gz(r-4.6-any)
finetune_1.3.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
finetune/json (API)

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

Bug tracker:https://github.com/tidymodels/finetune/issues

Pkgdown/docs site:https://finetune.tidymodels.org

On CRAN:

Conda:

9.69 score 65 stars 2 packages 1.1k scripts 4.8k downloads 6 exports 102 dependencies

Last updated from:552bcd9a24. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK234
source / vignettesOK291
linux-release-x86_64OK245
macos-release-arm64OK205
macos-oldrel-arm64OK154
windows-develOK181
windows-releaseOK156
windows-oldrelOK165
wasm-releaseOK160

Exports:control_racecontrol_sim_annealplot_racetune_race_anovatune_race_win_losstune_sim_anneal

Dependencies:base64encbslibcachemclasscliclockcodetoolscpp11data.tablediagramdialsDiceDesigndigestdplyrevaluatefarverfastmapfontawesomefsfurrrfuturefuture.applyGauProgenericsggplot2globalsgluegowergtablehardhathighrhtmltoolsipredisobandjquerylibjsonliteKernSmoothknitrlabelinglatticelavalbfgslifecyclelistenvlubridatemagrittrMASSMatrixmemoisemimemixoptmodelenvnnetnumDerivparallellyparsnippillarpkgconfigprettyunitsprodlimprogressrpurrrR6rappdirsRColorBrewerRcppRcppArmadillorecipesrlangrmarkdownrpartrsampleS7sassscalessfdshapeslidersparsevctrssplitfngrSQUAREMstringistringrsurvivaltailortibbletidyrtidyselecttimechangetimeDatetinytextunetzdbutf8vctrsviridisLitewarpwithrworkflowsxfunyamlyardstick

Readme and manuals

Help Manual

Help pageTopics
Obtain and format results produced by racing functionscollect_metrics.tune_race collect_predictions collect_predictions.tune_race
Control aspects of the grid search racing processcontrol_race
Control aspects of the simulated annealing search processcontrol_sim_anneal
Plot racing resultsplot_race
Investigate best tuning parametersshow_best.tune_race
Efficient grid search via racing with ANOVA modelstune_race_anova tune_race_anova.model_spec tune_race_anova.workflow
Efficient grid search via racing with win/loss statisticstune_race_win_loss tune_race_win_loss.model_spec tune_race_win_loss.workflow
Optimization of model parameters via simulated annealingtune_sim_anneal tune_sim_anneal.model_spec tune_sim_anneal.workflow