Man pages for bsnsing
Build Decision Trees with Optimal Multivariate Splits

binarizeCreate Binary Variables by the Classification Target
binarize.factorCreate Binary Features based on a Factor Vector
binarize.numericCreate Binary Features based on a Numeric Vector
binarize.yRecode a Variable with Two Unique Values into an 0/1 Vector
bscontrolDefine Parameters for the 'bsnsing' Fit
bslearnFind the Optimal Boolean Rule for Binary Classification
bsnsingLearn a Classification Tree using Boolean Sensing
bsnsing.defaultLearn a Classification Tree with Boolean Sensing
bsnsing.formulaLearn a Classification Tree using Boolean Sensing
bsnsing-packagebsnsing: Build Decision Trees with Optimal Multivariate...
import_external_rulesImport split rules from other packages
mbsnsing-classA class that contains multi-class classification model built...
plot.bsnsingGenerate latex code for plotting a bsnsing tree
plot.mbsnsingGenerate latex code for plotting an mbsnsing tree
predict.bsnsingMake Predictions with a Fitted 'bsnsing' Model
predict.mbsnsingMake Predictions with a 'bsnsing' Model
print.bscontrolPrint the Object of Class 'bscontrol'
print.bsnsingPrint the Object of Class 'bsnsing'
print.mbsnsingPrint the Object of Class 'mbsnsing'
print.summary.bsnsingPrint the Summary of 'bsnsing' Model
print.summary.mbsnsingPrint the summary of 'mbsnsing' model fits
rcpp_bslearnC implementation of the bslearn function
ROC_funcPlot the ROC curve and calculate the AUC
summary.bsnsingSummarize the bsnsing Model Fits
summary.mbsnsingSummarize mbsnsing Model Fits
bsnsing documentation built on July 4, 2022, 1:06 a.m.