cvms-package |
cvms: A package for cross-validating regression and classification models |
as.character.process_info_binomial |
A set of process information object constructors |
as.character.process_info_gaussian |
A set of process information object constructors |
as.character.process_info_multinomial |
A set of process information object constructors |
baseline |
Create baseline evaluations |
baseline_binomial |
Create baseline evaluations for binary classification |
baseline_gaussian |
Create baseline evaluations for regression models |
baseline_multinomial |
Create baseline evaluations |
binomial_metrics |
Select metrics for binomial evaluation |
combine_predictors |
Generate model formulas by combining predictors |
compatible.formula.terms |
Compatible formula terms |
confusion_matrix |
Create a confusion matrix |
cross_validate |
Cross-validate regression models for model selection |
cross_validate_fn |
Cross-validate custom model functions for model selection |
cvms |
cvms: A package for cross-validating regression and classification models |
evaluate |
Evaluate your model's performance |
evaluate_residuals |
Evaluate residuals from a regression task |
font |
Create a list of font settings for plots |
gaussian_metrics |
Select metrics for Gaussian evaluation |
generate_formulas |
Generate model formulas by combining predictors |
hardest |
Find the data points that were hardest to predict |
model_functions |
Examples of model_fn functions |
most_challenging |
Find the data points that were hardest to predict |
multiclass_probability_tibble |
Generate a multiclass probability tibble |
multinomial_metrics |
Select metrics for multinomial evaluation |
musicians |
Musician groups |
participant.scores |
Participant scores |
plot_confusion_matrix |
Plot a confusion matrix |
plot_metric_density |
Density plot for a metric |
precomputed.formulas |
Precomputed formulas |
predicted.musicians |
Predicted musician groups |
predict_functions |
Examples of predict_fn functions |
preprocess_functions |
Examples of preprocess_fn functions |
print.process_info_binomial |
A set of process information object constructors |
print.process_info_gaussian |
A set of process information object constructors |
print.process_info_multinomial |
A set of process information object constructors |
process_info_binomial |
A set of process information object constructors |
process_info_gaussian |
A set of process information object constructors |
process_info_multinomial |
A set of process information object constructors |
reconstruct_formulas |
Reconstruct model formulas from results tibbles |
select_definitions |
Select model definition columns |
select_metrics |
Select columns with evaluation metrics and model definitions |
simplify_formula |
Simplify formula with inline functions |
summarize_metrics |
Summarize metrics with common descriptors |
sum_tile_settings |
Create a list of settings for the sum tiles in plot_confusion_matrix() |
update_hyperparameters |
Check and update hyperparameters |
validate |
Validate regression models on a test set |
validate_fn |
Validate a custom model function on a test set |
wines |
Wine varieties |