Man pages for precrec
Calculate Accurate Precision-Recall and ROC (Receiver Operator Characteristics) Curves

as.data.frameConvert a curves and points object to a data frame
aucRetrieve a data frame of AUC scores
autoplotPlot performance evaluation measures with ggplot2
B1000Balanced data with 1000 positives and 1000 negatives.
B500Balanced data with 500 positives and 500 negatives.
create_sim_samplesCreate random samples for simulations
evalmodEvaluate models and calculate performance evaluation measures
format_nfoldCreate n-fold cross validation dataset from data frame
fortifyConvert a curves and points object to a data frame for...
IB1000Imbalanced data with 1000 positives and 10000 negatives.
IB500Imbalanced data with 500 positives and 5000 negatives.
join_labelsJoin observed labels of multiple test datasets into a list
join_scoresJoin scores of multiple models into a list
M2N50F55-fold cross validation sample.
mmdataReformat input data for performance evaluation calculation
P10N10A small example dataset with several tied scores.
partCalculate partial AUCs
paucRetrieve a data frame of pAUC scores
plotPlot performance evaluation measures
precrecprecrec: A package for computing accurate ROC and...
precrec documentation built on Aug. 23, 2017, 9:05 a.m.