Data Sets and Functions to Accompany "Tree-Based Methods for Statistical Learning in R"


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Documentation for package ‘treemisc’ version 0.0.1

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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