NCI60                   NCI60 Dataset
bag_samples             In-bag row indices per tree.
binarize_disabled       Disabled binarization strategy (placeholder).
binarize_largest_gap    Largest-gap binarization strategy.
california_housing      California Housing Dataset
crab                    Australian Crabs Dataset
crabs                   Crabs Dataset
cutpoint_mean_of_means
                        Mean-of-means split cutpoint strategy.
fishcatch               Fish Catch Dataset
fitted.ppmodel          Fitted (in-sample) predictions from a ppforest2
                        model.
formula.ppmodel         Formula extractor for ppforest2 models.
glass                   Glass Dataset
grouping_by_cutpoint    Cutpoint-based grouping strategy (regression).
grouping_by_label       Label-based grouping strategy.
image                   Image Dataset
leaf_majority_vote      Majority-vote leaf strategy.
leaf_mean_response      Mean-response leaf strategy.
leukemia                Leukemia Dataset
load_json               Load a model from a JSON file.
lymphoma                Lymphoma Dataset
nobs.ppmodel            Number of observations used to fit a ppforest2
                        model.
olive                   Olive Dataset
oob_error               Out-of-bag error for a random forest.
oob_predictions         Out-of-bag predictions for a random forest.
oob_samples             Out-of-bag row indices per tree.
parkinson               Parkinson Dataset
permuted_importance     Permuted variable importance for a random
                        forest.
plot.pprf               Plot a pprf model.
plot.pptr               Plot a pptr model.
pp_pda                  PDA projection pursuit strategy.
pp_rand_forest          Parsnip model specification for pprf.
pp_tree                 Parsnip model specification for pptr.
pprf                    Trains a Random Forest of Projection-Pursuit
                        oblique decision trees.
pptr                    Trains a Projection-Pursuit oblique decision
                        tree.
predict.pprf_classification
                        Predicts labels or vote proportions from a pprf
                        model (classification mode).
predict.pprf_regression
                        Predicts numeric responses from a pprf model
                        (regression mode).
predict.pptr_classification
                        Predicts labels or per-group one-hot
                        proportions from a pptr model (classification
                        mode).
predict.pptr_regression
                        Predicts numeric responses from a pptr model
                        (regression mode).
print.pprf              Prints a compact summary of a pprf forest.
print.pptr              Prints the structure of a pptr tree.
projection_importance   Projection-coefficient variable importance.
residuals.ppmodel       Residuals from a regression ppforest2 model.
save_json               Save a model to a JSON file.
stop_any                Composite stopping rule (logical OR).
stop_max_depth          Maximum-depth stopping rule.
stop_min_size           Minimum-size stopping rule.
stop_min_variance       Minimum-variance stopping rule.
stop_pure_node          Pure-node stopping rule.
summary.pprf            Summary of a pprf forest (shared header + VI).
update.pp_rand_forest   Update a 'pp_rand_forest' model specification.
update.pp_tree          Update a 'pp_tree' model specification.
vars_all                All-variables selection strategy.
vars_uniform            Uniform random variable selection strategy.
weighted_importance     Weighted projection variable importance for a
                        random forest.
wine                    Wine Dataset
