Man pages for yardstick
Tidy Characterizations of Model Performance

accuracy	Accuracy
average_precision	Area under the precision recall curve
bal_accuracy	Balanced accuracy
ccc	Concordance correlation coefficient
conf_mat	Confusion Matrix for Categorical Data
detection_prevalence	Detection prevalence
developer-helpers	Developer helpers
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
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_vec_template	Developer function for calling new metrics
mn_log_loss	Mean log loss
mpe	Mean percentage error
new-metric	Construct a new metric function
npv	Negative predictive value
pathology	Liver Pathology 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_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
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