Package: finetune 1.2.0.9000

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) <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_1.2.0.9000.tar.gz
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finetune.pdf |finetune.html✨
finetune/json (API)
NEWS

# 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

On CRAN:

8.46 score 62 stars 708 scripts 1.6k downloads 6 exports 86 dependencies

Last updated 3 months agofrom:a016fba491. Checks:OK: 5 NOTE: 2. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 13 2024
R-4.5-win	NOTE	Nov 13 2024
R-4.5-linux	NOTE	Nov 13 2024
R-4.4-win	OK	Nov 13 2024
R-4.4-mac	OK	Nov 13 2024
R-4.3-win	OK	Nov 13 2024
R-4.3-mac	OK	Nov 13 2024

Exports:control_race control_sim_anneal plot_race tune_race_anova tune_race_win_loss tune_sim_anneal

Dependencies:class cli clock codetools colorspace cpp11 data.table diagram dials DiceDesign digest doFuture dplyr fansi farver foreach furrr future future.apply generics ggplot2 globals glue gower GPfit gtable hardhat ipred isoband iterators KernSmooth labeling lattice lava lhs lifecycle listenv lubridate magrittr MASS Matrix mgcv modelenv munsell nlme nnet numDeriv parallelly parsnip pillar pkgconfig prettyunits prodlim progressr purrr R6 RColorBrewer Rcpp recipes rlang rpart rsample scales sfd shape slider sparsevctrs SQUAREM stringi stringr survival tailor tibble tidyr tidyselect timechange timeDate tune tzdb utf8 vctrs viridisLite warp withr workflows yardstick

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Obtain and format results produced by racing functions	collect_metrics.tune_race collect_predictions collect_predictions.tune_race
Control aspects of the grid search racing process	control_race
Control aspects of the simulated annealing search process	control_sim_anneal
Plot racing results	plot_race
Investigate best tuning parameters	show_best.tune_race
Efficient grid search via racing with ANOVA models	tune_race_anova tune_race_anova.model_spec tune_race_anova.workflow
Efficient grid search via racing with win/loss statistics	tune_race_win_loss tune_race_win_loss.model_spec tune_race_win_loss.workflow
Optimization of model parameters via simulated annealing	tune_sim_anneal tune_sim_anneal.model_spec tune_sim_anneal.workflow