Package: yardstick 1.3.1.9000

Emil Hvitfeldt

yardstick:Tidy Characterizations of Model Performance

Tidy tools for quantifying how well model fits to a data set such as confusion matrices, class probability curve summaries, and regression metrics (e.g., RMSE).

Authors:Max Kuhn [aut], Davis Vaughan [aut], Emil Hvitfeldt [aut, cre], Posit Software, PBC [cph, fnd]

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yardstick/json (API)
NEWS

# Installyardstick in R:

install.packages('yardstick',repos = c('https://tidymodels.r-universe.dev', 'https://cloud.r-project.org'))

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

Datasets:

hpc_cv - Multiclass Probability Predictions
lung_surv - Survival Analysis Results
pathology - Liver Pathology Data
solubility_test - Solubility Predictions from MARS Model
two_class_example - Two Class Predictions

On CRAN:

129 exports 365 stars 7.79 score 17 dependencies 54 dependents 40.5k downloads

Last updated 3 months agofrom:be744a3d41

Exports:accuracy accuracy_vec average_precision average_precision_vec bal_accuracy bal_accuracy_vec brier_class brier_class_vec brier_survival brier_survival_integrated brier_survival_integrated_vec brier_survival_vec ccc ccc_vec check_class_metric check_dynamic_survival_metric check_numeric_metric check_prob_metric check_static_survival_metric class_metric_summarizer classification_cost classification_cost_vec concordance_survival concordance_survival_vec conf_mat curve_metric_summarizer curve_survival_metric_summarizer demographic_parity detection_prevalence detection_prevalence_vec dots_to_estimate dynamic_survival_metric_summarizer equal_opportunity equalized_odds f_meas f_meas_vec finalize_estimator finalize_estimator_internal gain_capture gain_capture_vec gain_curve get_weights huber_loss huber_loss_pseudo huber_loss_pseudo_vec huber_loss_vec iic iic_vec j_index j_index_vec kap kap_vec lift_curve mae mae_vec mape mape_vec mase mase_vec mcc mcc_vec metric_set metric_summarizer metric_tweak metric_vec_template metrics mn_log_loss mn_log_loss_vec mpe mpe_vec msd msd_vec new_class_metric new_dynamic_survival_metric new_groupwise_metric new_integrated_survival_metric new_numeric_metric new_prob_metric new_static_survival_metric npv npv_vec numeric_metric_summarizer poisson_log_loss poisson_log_loss_vec ppv ppv_vec pr_auc pr_auc_vec pr_curve precision precision_vec prob_metric_summarizer recall recall_vec rmse rmse_vec roc_auc roc_auc_survival roc_auc_survival_vec roc_auc_vec roc_aunp roc_aunp_vec roc_aunu roc_aunu_vec roc_curve roc_curve_survival rpd rpd_vec rpiq rpiq_vec rsq rsq_trad rsq_trad_vec rsq_vec sens sens_vec sensitivity sensitivity_vec smape smape_vec spec spec_vec specificity specificity_vec static_survival_metric_summarizer tidy validate_estimator yardstick_any_missing yardstick_remove_missing

Dependencies:cli dplyr fansi generics glue hardhat lifecycle magrittr pillar pkgconfig R6 rlang tibble tidyselect utf8 vctrs withr

Grouping behavior in yardstick

Simon Couch

Rendered fromgrouping.Rmdusingknitr::rmarkdownon Jun 19 2024.

Last update: 2023-11-02
Started: 2023-11-02

Metric types

Davis Vaughan

Rendered frommetric-types.Rmdusingknitr::rmarkdownon Jun 19 2024.

Last update: 2024-04-02
Started: 2018-11-01

Multiclass averaging

Davis Vaughan

Rendered frommulticlass.Rmdusingknitr::rmarkdownon Jun 19 2024.

Last update: 2022-11-23
Started: 2018-11-01

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Accuracy	accuracy accuracy.data.frame accuracy_vec
Area under the precision recall curve	average_precision average_precision.data.frame average_precision_vec
Balanced accuracy	bal_accuracy bal_accuracy.data.frame bal_accuracy_vec
Brier score for classification models	brier_class brier_class.data.frame brier_class_vec
Time-Dependent Brier score for right censored data	brier_survival brier_survival.data.frame brier_survival_vec
Integrated Brier score for right censored data	brier_survival_integrated brier_survival_integrated.data.frame brier_survival_integrated_vec
Concordance correlation coefficient	ccc ccc.data.frame ccc_vec
Developer function for checking inputs in new metrics	check_class_metric check_dynamic_survival_metric check_metric check_numeric_metric check_prob_metric check_static_survival_metric
Costs function for poor classification	classification_cost classification_cost.data.frame classification_cost_vec
Concordance index for right-censored data	concordance_survival concordance_survival.data.frame concordance_survival_vec
Confusion Matrix for Categorical Data	conf_mat conf_mat.data.frame conf_mat.default conf_mat.table tidy.conf_mat
Demographic parity	demographic_parity
Detection prevalence	detection_prevalence detection_prevalence.data.frame detection_prevalence_vec
Developer helpers	developer-helpers dots_to_estimate finalize_estimator finalize_estimator_internal get_weights validate_estimator
Equal opportunity	equal_opportunity
Equalized odds	equalized_odds
F Measure	f_meas f_meas.data.frame f_meas_vec
Gain capture	gain_capture gain_capture.data.frame gain_capture_vec
Gain curve	gain_curve gain_curve.data.frame
Multiclass Probability Predictions	hpc_cv
Huber loss	huber_loss huber_loss.data.frame huber_loss_vec
Psuedo-Huber Loss	huber_loss_pseudo huber_loss_pseudo.data.frame huber_loss_pseudo_vec
Index of ideality of correlation	iic iic.data.frame iic_vec
J-index	j_index j_index.data.frame j_index_vec
Kappa	kap kap.data.frame kap_vec
Lift curve	lift_curve lift_curve.data.frame
Survival Analysis Results	lung_surv
Mean absolute error	mae mae.data.frame mae_vec
Mean absolute percent error	mape mape.data.frame mape_vec
Mean absolute scaled error	mase mase.data.frame mase_vec
Matthews correlation coefficient	mcc mcc.data.frame mcc_vec
Combine metric functions	metric_set
Tweak a metric function	metric_tweak
Developer function for summarizing new metrics	class_metric_summarizer curve_metric_summarizer curve_survival_metric_summarizer dynamic_survival_metric_summarizer metric-summarizers numeric_metric_summarizer prob_metric_summarizer static_survival_metric_summarizer
General Function to Estimate Performance	metrics metrics.data.frame
Mean log loss for multinomial data	mn_log_loss mn_log_loss.data.frame mn_log_loss_vec
Mean percentage error	mpe mpe.data.frame mpe_vec
Mean signed deviation	msd msd.data.frame msd_vec
Create groupwise metrics	new_groupwise_metric
Construct a new metric function	new-metric new_class_metric new_dynamic_survival_metric new_integrated_survival_metric new_numeric_metric new_prob_metric new_static_survival_metric
Negative predictive value	npv npv.data.frame npv_vec
Liver Pathology Data	pathology
Mean log loss for Poisson data	poisson_log_loss poisson_log_loss.data.frame poisson_log_loss_vec
Positive predictive value	ppv ppv.data.frame ppv_vec
Area under the precision recall curve	pr_auc pr_auc.data.frame pr_auc_vec
Precision recall curve	pr_curve pr_curve.data.frame
Precision	precision precision.data.frame precision_vec
Recall	recall recall.data.frame recall_vec
Root mean squared error	rmse rmse.data.frame rmse_vec
Area under the receiver operator curve	roc_auc roc_auc.data.frame roc_auc_vec
Time-Dependent ROC AUC for Censored Data	roc_auc_survival roc_auc_survival.data.frame roc_auc_survival_vec
Area under the ROC curve of each class against the rest, using the a priori class distribution	roc_aunp roc_aunp.data.frame roc_aunp_vec
Area under the ROC curve of each class against the rest, using the uniform class distribution	roc_aunu roc_aunu.data.frame roc_aunu_vec
Receiver operator curve	roc_curve roc_curve.data.frame
Time-Dependent ROC surve for Censored Data	roc_curve_survival roc_curve_survival.data.frame
Ratio of performance to deviation	rpd rpd.data.frame rpd_vec
Ratio of performance to inter-quartile	rpiq rpiq.data.frame rpiq_vec
R squared	rsq rsq.data.frame rsq_vec
R squared - traditional	rsq_trad rsq_trad.data.frame rsq_trad_vec
Sensitivity	sens sens.data.frame sensitivity sensitivity.data.frame sensitivity_vec sens_vec
Symmetric mean absolute percentage error	smape smape.data.frame smape_vec
Solubility Predictions from MARS Model	solubility_test
Specificity	spec spec.data.frame specificity specificity.data.frame specificity_vec spec_vec
Summary Statistics for Confusion Matrices	summary.conf_mat
Two Class Predictions	two_class_example
Developer function for handling missing values in new metrics	yardstick_any_missing yardstick_remove_missing