Tidy Characterizations of Model Performance
Accuracy
Area under the precision recall curve
Balanced accuracy
Brier score for classification models
Integrated Brier score for right censored data
Time-Dependent Brier score for right censored data
Concordance correlation coefficient
Developer function for checking inputs in new metrics
Costs function for poor classification
Concordance index for right-censored data
Confusion Matrix for Categorical Data
Demographic parity
Detection prevalence
Developer helpers
Equal opportunity
Equalized odds
F Measure
Gain capture
Gain curve
Psuedo-Huber Loss
Huber loss
Index of ideality of correlation
J-index
Kappa
Lift curve
Mean absolute error
Mean absolute percent error
Mean absolute scaled error
Matthews correlation coefficient
Combine metric functions
Developer function for summarizing new metrics
Tweak a metric function
Developer function for calling new metrics
Developer function for summarizing new metrics
General Function to Estimate Performance
Mean log loss for multinomial data
Mean percentage error
Mean signed deviation
Create groupwise metrics
Construct a new metric function
Negative predictive value
Mean log loss for Poisson data
Positive predictive value
Area under the precision recall curve
Precision recall curve
Precision
Recall
Objects exported from other packages
Root mean squared error
Time-Dependent ROC AUC for Censored Data
Area under the receiver operator curve
Area under the ROC curve of each class against the rest, using the a p...
Area under the ROC curve of each class against the rest, using the uni...
Time-Dependent ROC surve for Censored Data
Receiver operator curve
Ratio of performance to deviation
Ratio of performance to inter-quartile
R squared - traditional
R squared
Sensitivity
Symmetric mean absolute percentage error
Specificity
Summary Statistics for Confusion Matrices
Developer function for handling missing values in new metrics
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).
Useful links