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 |

bsnsing-package | bsnsing: Build Decision Trees with Optimal Multivariate... |

GlaucomaMVF | GlaucomaMVF |

import_external_rules | Import split rules from other packages |

iris | iris |

mbsnsing-class | A class that contains multi-class classification model built... |

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 |

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