R: Build Decision Trees with Optimal Multivariate Splits

# Build Decision Trees with Optimal Multivariate Splits

## Documentation for package ‘bsnsing’ version 1.0.1

- DESCRIPTION file.

## Help Pages

bsnsing-package | bsnsing: Build Decision Trees with Optimal Multivariate Splits
auto | auto
binarize | Create Binary Variables by the Classification Target
binarize.factor | Create Binary Features based on a Factor Vector
binarize.numeric | Create Binary Features based on a Numeric Vector
binarize.y | Recode a Variable with Two Unique Values into an 0/1 Vector
BreastCancer | BreastCancer
bscontrol | Define Parameters for the 'bsnsing' Fit
bslearn | Find the Optimal Boolean Rule for Binary Classification
bsnsing | Learn a Classification Tree using Boolean Sensing
bsnsing.default | Learn a Classification Tree with Boolean Sensing
bsnsing.formula | Learn a Classification Tree using Boolean Sensing
GlaucomaMVF | GlaucomaMVF
import_external_rules | Import split rules from other packages
iris | iris
mbsnsing | A class that contains multi-class classification model built by bsnsing. Can be used in summary and predict functions.
mbsnsing-class | A class that contains multi-class classification model built by bsnsing. Can be used in summary and predict functions.
plot.bsnsing | Generate latex code for plotting a bsnsing tree
plot.mbsnsing | Generate latex code for plotting an mbsnsing tree
predict.bsnsing | Make Predictions with a Fitted 'bsnsing' Model
predict.mbsnsing | Make Predictions with a 'bsnsing' Model
print.bscontrol | Print the Object of Class 'bscontrol'
print.bsnsing | Print the Object of Class 'bsnsing'
print.mbsnsing | Print the Object of Class 'mbsnsing'
print.summary.bsnsing | Print the Summary of 'bsnsing' Model
print.summary.mbsnsing | Print the summary of 'mbsnsing' model fits
rcpp_bslearn | C implementation of the bslearn function
ROC_func | Plot the ROC curve and calculate the AUC
summary.bsnsing | Summarize the bsnsing Model Fits
summary.mbsnsing | Summarize mbsnsing Model Fits