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cvms  

Cross-Validation for Model Selection
View on CRAN: Click here


Download and install cvms package within the R console
Install from CRAN:
install.packages("cvms")

Install from Github:
library("remotes")
install_github("cran/cvms")

Install by package version:
library("remotes")
install_version("cvms", "1.6.2")



Attach the package and use:
library("cvms")
Maintained by
Ludvig Renbo Olsen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-07-02
Latest Update: 2024-02-27
Description:
Cross-validate one or multiple regression and classification models and get relevant evaluation metrics in a tidy format. Validate the best model on a test set and compare it to a baseline evaluation. Alternatively, evaluate predictions from an external model. Currently supports regression and classification (binary and multiclass). Described in chp. 5 of Jeyaraman, B. P., Olsen, L. R., & Wambugu M. (2019, ISBN: 9781838550134).
How to cite:
Ludvig Renbo Olsen (2019). cvms: Cross-Validation for Model Selection. R package version 1.6.2, https://cran.r-project.org/web/packages/cvms. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.1.0 (2019-07-02 17:10), 0.1.1 (2019-07-20 15:50), 0.1.2 (2019-08-05 16:50), 0.2.0 (2019-09-07 18:20), 0.3.0 (2019-09-29 06:20), 0.3.1 (2019-10-03 12:50), 0.3.2 (2019-12-02 00:10), 1.0.0 (2020-04-14 08:50), 1.0.1 (2020-04-19 11:30), 1.0.2 (2020-05-29 02:00), 1.1.0 (2020-10-07 23:20), 1.2.0 (2020-10-18 23:50), 1.2.1 (2021-02-17 15:00), 1.3.0 (2021-06-07 16:40), 1.3.1 (2021-06-17 13:00), 1.3.2 (2021-10-06 16:10), 1.3.3 (2021-11-14 18:20), 1.3.4 (2022-07-15 16:40), 1.3.5 (2022-08-26 15:54), 1.3.6 (2022-10-12 14:42), 1.3.7 (2022-11-24 01:20), 1.3.8 (2023-01-05 22:00), 1.3.9 (2023-01-26 16:00), 1.4.0 (2023-06-04 16:10), 1.4.1 (2023-06-11 10:20), 1.5.0 (2023-06-18 13:50), 1.6.0 (2023-06-29 23:50), 1.6.1 (2024-02-27 21:50)
Other packages that cited cvms R package
View cvms citation profile
Other R packages that cvms depends, imports, suggests or enhances
Complete documentation for cvms
Functions, R codes and Examples using the cvms R package
Some associated functions: baseline . baseline_binomial . baseline_gaussian . baseline_multinomial . binomial_metrics . combine_predictors . compatible.formula.terms . confusion_matrix . cross_validate . cross_validate_fn . cvms . evaluate . evaluate_residuals . font . gaussian_metrics . model_functions . most_challenging . multiclass_probability_tibble . multinomial_metrics . musicians . participant.scores . plot_confusion_matrix . plot_metric_density . plot_probabilities . plot_probabilities_ecdf . precomputed.formulas . predict_functions . predicted.musicians . preprocess_functions . process_info_binomial . reconstruct_formulas . render_toc . select_definitions . select_metrics . simplify_formula . sum_tile_settings . summarize_metrics . update_hyperparameters . validate . validate_fn . wines . 
Some associated R codes: baseline.R . baseline_binomial.R . baseline_gaussian.R . baseline_multinomial.R . baseline_wrappers.R . call_validate.R . choosing_metrics_functions.R . combine_predictors.R . combine_predictors_prepare_args.R . computational_grid.R . confusion_matrix.R . cross_validate.R . cross_validate_fn.R . cross_validate_list.R . data_documentation.R . evaluate.R . evaluate_predictions_binomial.R . evaluate_predictions_gaussian.R . evaluate_predictions_multinomial.R . evaluate_residuals.R . extract_model_effects.R . extract_probabilities_of.R . extract_special_fn_specific_hparams.R . fit_model.R . fit_predict_model_fn.R . get_nested_model_coefficients.R . helpers.R . internal_evaluate_model.R . internal_evaluate_predictions.R . metrics.R . model_functions.R . most_challenging.R . multiclass_probability_tibble.R . nesting_predictions.R . package_info.R . plot_confusion_matrix.R . plot_metric_density.R . plot_probabilities.R . plot_probabilities_ecdf.R . plot_probability_violins.R . plotting_utilities.R . predict_functions.R . prepare_evaluation.R . prepare_train_test.R . preprocess_functions.R . process_info.R . reconstruct_formulas.R . run_model_fitting.R . run_prediction_process.R . run_quietly.R . select_definitions.R . select_metrics.R . set_info_cols.R . set_metrics.R . simplify_formula.R . softmax.R . summarize_metrics.R . table_of_content_markdown.R . update_hyperparameters.R . update_model_specifics.R . validate.R . validate_fn.R . validate_fold.R . validate_list.R .  Full cvms package functions and examples
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