Release yardstick 1.4.0 · tidymodels/yardstick

Breaking Changes

The global option yardstick.event_first (deprecated in 0.0.7) now throws an error. Use the event_level argument of individual metric functions instead. (#632)
conf_mat() now throws an error if anything is passed to ... (deprecated in 1.0.0). This argument has had no effect since case weight support was added. (#632)
roc_auc(), roc_aunp(), roc_aunu(), and roc_curve() now throw an error if a non-empty list is passed to options (deprecated in 1.0.0). Use the pROC package directly if you need these features. (#632)

dots_to_estimate(), metric_summarizer(), and metric_vec_template() (soft-deprecated in 1.2.0) now warn for all users. See the yardstick 1.2.0 release notes for recommended replacements. (#632)

gini_coef() computes the normalized Gini coefficient for regression, which measures ranking ability based on the Lorenz curve. (#147)
mse() computes the mean squared error. (#560)
rmse_relative() computes the relative root mean squared error, normalizing RMSE by the range of the true values. (#527)
fall_out() and miss_rate() compute the false positive rate and false negative rate respectively. (#336)
markedness() computes the markedness metric (PPV + NPV - 1), the predictive power analog of j_index(). (#27)
roc_dist() computes the Euclidean distance from the (sensitivity, specificity) point to the ideal point (1, 1) in ROC space. (#148)
sedi() computes the Symmetric Extremal Dependence Index, a prevalence-independent skill metric for binary classification that remains reliable at extreme class imbalance. (#630)
ranked_prob_score() computes the ranked probability score for ordinal classification data. (#524)
weighted_interval_score() is a new quantile metric. (#569)

Added checks to all metrics for the na_rm argument. (#349)
Added improved argument checking for metrics with additional arguments. (#519)
Added documentation pages for each metric type (e.g., ?class-metrics, ?numeric-metrics) listing all available metrics with their direction and range. (#547, #540)
All class metrics and probability metrics now include mathematical formulas in their documentation. (#605)
All metrics now document their valid range of output values. (#572)
Documentation pages for metrics with alternate argument values now emphasize using metric_tweak() when building metric sets. (#626)
Survival metrics performance has been improved. (#576)
brier_class() has gained the event_level argument. (#515)
get_metrics() has been added to return a metric_set() containing all metrics of a specified type. (#534)
metric_set() now provides a more informative error message when estimate is not explicitly named for class/prob or survival metric sets. (#504)
roc_curve() has gained a thresholds argument for specifying custom thresholds at which the curve is evaluated. (#488)

brier_class() no longer returns NaN with extreme value case weights. (#614)
classification_cost() documentation now correctly refers to the cost column of the costs data frame. (#343)
mpe() documentation now includes the formula and clarifies the interpretation of positive and negative values. (#345)
poisson_log_loss() now handles 0-valued estimates without returning Inf or NaN. (#513)
Fixed a bug where ranked probability metrics didn't work in combination with other classification metrics in metric_set(). (#539)
Fixed documentation to show equations correctly. (#541)

Added infrastructure for quantile metrics. (#569)
Added infrastructure for survival metrics on the linear predictor. (#551)
new_metric() and related functions gain an optional range argument to store the valid output range of a metric. (#572)
Removed crayon as a suggested package. (#574)