Calculate Accurate Precision-Recall and ROC (Receiver Operator Characteristics) Curves

as.data.frame | Convert a curves and points object to a data frame |

auc | Retrieve a data frame of AUC scores |

auc_ci | Calculate CIs of ROC and precision-recall AUCs |

autoplot | Plot performance evaluation measures with ggplot2 |

B1000 | Balanced data with 1000 positives and 1000 negatives. |

B500 | Balanced data with 500 positives and 500 negatives. |

create_sim_samples | Create random samples for simulations |

evalmod | Evaluate models and calculate performance evaluation measures |

format_nfold | Create n-fold cross validation dataset from data frame |

fortify | Convert a curves and points object to a data frame for... |

IB1000 | Imbalanced data with 1000 positives and 10000 negatives. |

IB500 | Imbalanced data with 500 positives and 5000 negatives. |

join_labels | Join observed labels of multiple test datasets into a list |

join_scores | Join scores of multiple models into a list |

M2N50F5 | 5-fold cross validation sample. |

mmdata | Reformat input data for performance evaluation calculation |

P10N10 | A small example dataset with several tied scores. |

part | Calculate partial AUCs |

pauc | Retrieve a data frame of pAUC scores |

plot | Plot performance evaluation measures |

precrec | precrec: A package for computing accurate ROC and... |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.