as.data.frame |
Convert a curves and points object to a data frame |
as.data.frame.aucroc |
Convert a curves and points object to a data frame |
as.data.frame.mmcurves |
Convert a curves and points object to a data frame |
as.data.frame.mmpoints |
Convert a curves and points object to a data frame |
as.data.frame.mscurves |
Convert a curves and points object to a data frame |
as.data.frame.mspoints |
Convert a curves and points object to a data frame |
as.data.frame.smcurves |
Convert a curves and points object to a data frame |
as.data.frame.smpoints |
Convert a curves and points object to a data frame |
as.data.frame.sscurves |
Convert a curves and points object to a data frame |
as.data.frame.sspoints |
Convert a curves and points object to a data frame |
auc |
Retrieve a data frame of AUC scores |
auc.aucs |
Retrieve a data frame of AUC scores |
auc_ci |
Calculate CIs of ROC and precision-recall AUCs |
auc_ci.aucs |
Calculate CIs of ROC and precision-recall AUCs |
autoplot |
Plot performance evaluation measures with ggplot2 |
autoplot.mmcurves |
Plot performance evaluation measures with ggplot2 |
autoplot.mmpoints |
Plot performance evaluation measures with ggplot2 |
autoplot.mscurves |
Plot performance evaluation measures with ggplot2 |
autoplot.mspoints |
Plot performance evaluation measures with ggplot2 |
autoplot.smcurves |
Plot performance evaluation measures with ggplot2 |
autoplot.smpoints |
Plot performance evaluation measures with ggplot2 |
autoplot.sscurves |
Plot performance evaluation measures with ggplot2 |
autoplot.sspoints |
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 ggplot2 |
fortify.mmcurves |
Convert a curves and points object to a data frame for ggplot2 |
fortify.mmpoints |
Convert a curves and points object to a data frame for ggplot2 |
fortify.mscurves |
Convert a curves and points object to a data frame for ggplot2 |
fortify.mspoints |
Convert a curves and points object to a data frame for ggplot2 |
fortify.smcurves |
Convert a curves and points object to a data frame for ggplot2 |
fortify.smpoints |
Convert a curves and points object to a data frame for ggplot2 |
fortify.sscurves |
Convert a curves and points object to a data frame for ggplot2 |
fortify.sspoints |
Convert a curves and points object to a data frame for ggplot2 |
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 |
part.mmcurves |
Calculate partial AUCs |
part.mscurves |
Calculate partial AUCs |
part.smcurves |
Calculate partial AUCs |
part.sscurves |
Calculate partial AUCs |
pauc |
Retrieve a data frame of pAUC scores |
pauc.aucs |
Retrieve a data frame of pAUC scores |
plot |
Plot performance evaluation measures |
plot.mmcurves |
Plot performance evaluation measures |
plot.mmpoints |
Plot performance evaluation measures |
plot.mscurves |
Plot performance evaluation measures |
plot.mspoints |
Plot performance evaluation measures |
plot.smcurves |
Plot performance evaluation measures |
plot.smpoints |
Plot performance evaluation measures |
plot.sscurves |
Plot performance evaluation measures |
plot.sspoints |
Plot performance evaluation measures |
precrec |
precrec: A package for computing accurate ROC and Precision-Recall curves |