Package: tune 1.2.1.9000
Max Kuhn
tune: Tidy Tuning Tools
The ability to tune models is important. 'tune' contains functions and classes to be used in conjunction with other 'tidymodels' packages for finding reasonable values of hyper-parameters in models, pre-processing methods, and post-processing steps.
Authors:
tune_1.2.1.9000.tar.gz
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tune_1.2.1.9000.tgz(r-4.4-any)tune_1.2.1.9000.tgz(r-4.3-any)
tune_1.2.1.9000.tar.gz(r-4.5-noble)tune_1.2.1.9000.tar.gz(r-4.4-noble)
tune_1.2.1.9000.tgz(r-4.4-emscripten)tune_1.2.1.9000.tgz(r-4.3-emscripten)
tune.pdf |tune.html✨
tune/json (API)
NEWS
| # Install 'tune' in R: |
| install.packages('tune', repos = c('https://tidymodels.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tidymodels/tune/issues
- ames_grid_search - Example Analysis of Ames Housing Data
- ames_iter_search - Example Analysis of Ames Housing Data
- ames_wflow - Example Analysis of Ames Housing Data
Last updated 12 hours agofrom:f6772f4720. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 21 2024 |
| R-4.5-win | OK | Nov 21 2024 |
| R-4.5-linux | OK | Nov 21 2024 |
| R-4.4-win | OK | Nov 21 2024 |
| R-4.4-mac | OK | Nov 21 2024 |
| R-4.3-win | OK | Nov 21 2024 |
| R-4.3-mac | OK | Nov 21 2024 |
Exports:.catch_and_log.catch_and_log_fit.config_key_from_metrics.estimate_metrics.filter_perf_metrics.get_extra_col_names.get_fingerprint.get_tune_eval_time_target.get_tune_eval_times.get_tune_metric_names.get_tune_metrics.get_tune_outcome_names.get_tune_parameter_names.get_tune_parameters.get_tune_workflow.load_namespace.stash_last_result.use_case_weights_with_yardstickaugmentautoplotcheck_eval_time_argcheck_initialcheck_metric_in_tune_resultscheck_metricscheck_metrics_argcheck_parameterscheck_rsetcheck_timecheck_workflowchoose_eval_timechoose_metriccollect_extractscollect_metricscollect_notescollect_predictionscompute_metricsconf_boundconf_mat_resampledcontrol_bayescontrol_gridcontrol_last_fitcontrol_resamplescoord_obs_predempty_ellipsesencode_setestimate_tune_resultsexp_improveexpo_decayextract_fit_engineextract_fit_parsnipextract_modelextract_moldextract_parameter_set_dialsextract_preprocessorextract_recipeextract_spec_parsnipextract_workflowfilter_parametersfinalize_modelfinalize_recipefinalize_workflowfinalize_workflow_preprocessorfirst_eval_timefirst_metricfit_bestfit_max_valuefit_resamplesforge_from_workflowget_metric_timeget_tune_colorsinitialize_catalogint_pctlis_preprocessoris_recipeis_workflowlast_fitload_pkgsmaybe_choose_eval_timemessage_wrapmetrics_infomin_gridmin_grid.boost_treemin_grid.C5_rulesmin_grid.cubist_rulesmin_grid.linear_regmin_grid.logistic_regmin_grid.marsmin_grid.multinom_regmin_grid.nearest_neighbormin_grid.plsmin_grid.poisson_regmin_grid.rule_fitnew_backend_optionsnew_iteration_resultsoutcome_namesparametersprob_improvepull_rset_attributesrequired_pkgsselect_bestselect_by_one_std_errselect_by_pct_lossshow_bestshow_notestunabletunetune_argstune_bayestune_gridval_class_and_singleval_class_or_null
Dependencies:classcliclockcodetoolscolorspacecpp11data.tablediagramdialsDiceDesigndigestdoFuturedplyrfansifarverforeachfurrrfuturefuture.applygenericsggplot2globalsgluegowerGPfitgtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalhslifecyclelistenvlubridatemagrittrMASSMatrixmgcvmodelenvmunsellnlmennetnumDerivparallellyparsnippillarpkgconfigprettyunitsprodlimprogressrpurrrR6RColorBrewerRcpprecipesrlangrpartrsamplescalessfdshapeslidersparsevctrsSQUAREMstringistringrsurvivaltailortibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewarpwithrworkflowsyardstick
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Save most recent results to search path | .stash_last_result |
| Determine if case weights should be passed on to yardstick | .use_case_weights_with_yardstick .use_case_weights_with_yardstick.hardhat_frequency_weights .use_case_weights_with_yardstick.hardhat_importance_weights |
| Augment data with holdout predictions | augment.last_fit augment.resample_results augment.tune_results |
| Plot tuning search results | autoplot.tune_results |
| Obtain and format results produced by tuning functions | collect_extracts collect_extracts.tune_results collect_metrics collect_metrics.tune_results collect_notes collect_notes.tune_results collect_predictions collect_predictions.default collect_predictions.tune_results |
| Calculate and format metrics from tuning functions | compute_metrics compute_metrics.default compute_metrics.tune_results |
| Compute average confusion matrix across resamples | conf_mat_resampled |
| Control aspects of the Bayesian search process | control_bayes |
| Control aspects of the last fit process | control_last_fit |
| Use same scale for plots of observed vs predicted values | coord_obs_pred |
| Example Analysis of Ames Housing Data | ames_grid_search ames_iter_search ames_wflow example_ames_knn |
| Exponential decay function | expo_decay |
| Convenience functions to extract model | extract_model |
| Extract elements of 'tune' objects | extract-tune extract_fit_engine.tune_results extract_fit_parsnip.tune_results extract_mold.tune_results extract_preprocessor.tune_results extract_recipe.tune_results extract_spec_parsnip.tune_results extract_workflow.last_fit extract_workflow.tune_results |
| Remove some tuning parameter results | filter_parameters |
| Splice final parameters into objects | finalize_model finalize_recipe finalize_workflow |
| Fit a model to the numerically optimal configuration | fit_best fit_best.default fit_best.tune_results |
| Fit multiple models via resampling | fit_resamples fit_resamples.model_spec fit_resamples.workflow |
| Bootstrap confidence intervals for performance metrics | int_pctl.tune_results |
| Fit the final best model to the training set and evaluate the test set | last_fit last_fit.model_spec last_fit.workflow |
| Write a message that respects the line width | message_wrap |
| Support for parallel processing in tune | parallelism |
| Acquisition function for scoring parameter combinations | conf_bound exp_improve prob_improve |
| Investigate best tuning parameters | select_best select_best.default select_best.tune_results select_by_one_std_err select_by_one_std_err.default select_by_one_std_err.tune_results select_by_pct_loss select_by_pct_loss.default select_by_pct_loss.tune_results show_best show_best.default show_best.tune_results |
| Display distinct errors from tune objects | show_notes |
| Bayesian optimization of model parameters. | tune_bayes tune_bayes.model_spec tune_bayes.workflow |
| Model tuning via grid search | tune_grid tune_grid.model_spec tune_grid.workflow |
