Man pages for yardstick
Tidy Characterizations of Model Performance
| accuracy | Accuracy |
| average_precision | Area under the precision recall curve |
| bal_accuracy | Balanced accuracy |
| brier_class | Brier score for classification models |
| brier_survival | Time-Dependent Brier score for right censored data |
| brier_survival_integrated | Integrated Brier score for right censored data |
| ccc | Concordance correlation coefficient |
| check_metric | Developer function for checking inputs in new metrics |
| classification_cost | Costs function for poor classification |
| concordance_survival | Concordance index for right-censored data |
| conf_mat | Confusion Matrix for Categorical Data |
| demographic_parity | Demographic parity |
| detection_prevalence | Detection prevalence |
| developer-helpers | Developer helpers |
| equalized_odds | Equalized odds |
| equal_opportunity | Equal opportunity |
| f_meas | F Measure |
| gain_capture | Gain capture |
| gain_curve | Gain curve |
| hpc_cv | Multiclass Probability Predictions |
| huber_loss | Huber loss |
| huber_loss_pseudo | Psuedo-Huber Loss |
| iic | Index of ideality of correlation |
| j_index | J-index |
| kap | Kappa |
| lift_curve | Lift curve |
| lung_surv | Survival Analysis Results |
| mae | Mean absolute error |
| mape | Mean absolute percent error |
| mase | Mean absolute scaled error |
| mcc | Matthews correlation coefficient |
| metrics | General Function to Estimate Performance |
| metric_set | Combine metric functions |
| metric_summarizer | Developer function for summarizing new metrics |
| metric-summarizers | Developer function for summarizing new metrics |
| metric_tweak | Tweak a metric function |
| metric_vec_template | Developer function for calling new metrics |
| mn_log_loss | Mean log loss for multinomial data |
| mpe | Mean percentage error |
| msd | Mean signed deviation |
| new_groupwise_metric | Create groupwise metrics |
| new-metric | Construct a new metric function |
| npv | Negative predictive value |
| pathology | Liver Pathology Data |
| poisson_log_loss | Mean log loss for Poisson data |
| ppv | Positive predictive value |
| pr_auc | Area under the precision recall curve |
| pr_curve | Precision recall curve |
| precision | Precision |
| recall | Recall |
| reexports | Objects exported from other packages |
| rmse | Root mean squared error |
| roc_auc | Area under the receiver operator curve |
| roc_auc_survival | Time-Dependent ROC AUC for Censored Data |
| roc_aunp | Area under the ROC curve of each class against the rest,... |
| roc_aunu | Area under the ROC curve of each class against the rest,... |
| roc_curve | Receiver operator curve |
| roc_curve_survival | Time-Dependent ROC surve for Censored Data |
| rpd | Ratio of performance to deviation |
| rpiq | Ratio of performance to inter-quartile |
| rsq | R squared |
| rsq_trad | R squared - traditional |
| sens | Sensitivity |
| smape | Symmetric mean absolute percentage error |
| solubility_test | Solubility Predictions from MARS Model |
| spec | Specificity |
| summary.conf_mat | Summary Statistics for Confusion Matrices |
| two_class_example | Two Class Predictions |
| yardstick-package | yardstick: Tidy Characterizations of Model Performance |
| yardstick_remove_missing | Developer function for handling missing values in new metrics |
