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 |