treemisc-package | Data Sets and Functions to Accompany "Tree-Based Methods for Statistical Learning in R" |
banknote | Swiss banknote data |
banknote2 | Swiss banknote data (UCI version) |
calibrate | External probability calibration |
cummean | Cumulative means |
decision_boundary | Add decision boundary to a scatterplot. |
decision_boundary.default | Add decision boundary to a scatterplot. |
gbm_2way | Two-way interactions |
gen_friedman1 | Friedman benchmark data |
gen_mease | Generate data from the Mease model |
guide_setup | Generate GUIDE input files |
hitters | Baseball data (corrected) |
isle_post | Importance sampled learning ensemble |
ladboost | Gradient tree boosting with least absolute deviation (LAD) loss |
lift | Gain and lift charts |
load_eslmix | Gaussian mixture data |
lsboost | Gradient tree boosting with least squares (LS) loss |
mushroom | Mushroom edibility |
plot.calibrate | External probability calibration |
plot.lift | Gain and lift charts |
predict.ladboost | Gradient tree boosting with least absolute deviation (LAD) loss |
predict.lsboost | Gradient tree boosting with least squares (LS) loss |
predict.rforest | Random forest predictions |
print.calibrate | External probability calibration |
print.ladboost | Gradient tree boosting with least absolute deviation (LAD) loss |
print.lsboost | Gradient tree boosting with least squares (LS) loss |
proximity | Proximity matrix |
proximity.default | Proximity matrix |
proximity.matrix | Proximity matrix |
proximity.ranger | Proximity matrix |
prune_se | Prune an 'rpart' object |
rforest | Random forest |
rrm | Random rotation matrix |
treemisc | Data Sets and Functions to Accompany "Tree-Based Methods for Statistical Learning in R" |
tree_diagram | Tree diagram |
wilson_hilferty | Modified Wilson-Hilferty approximation |
wine | Wine quality |
xy_grid | Create a Cartesian product from evenly spaced values of two variables |
xy_grid.data.frame | Create a Cartesian product from evenly spaced values of two variables |
xy_grid.default | Create a Cartesian product from evenly spaced values of two variables |
xy_grid.formula | Create a Cartesian product from evenly spaced values of two variables |
xy_grid.matrix | Create a Cartesian product from evenly spaced values of two variables |