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 |