NA, you
only calculate an aggregated value. If you can define a function that makes sense
for every single training / test set, implement your own Measure.makeCustomResampledMeasure(id, minimize = TRUE, properties = character(0L),
fun, extra.args = list(), best = NULL, worst = NULL)Measure].G1, G2,
acc, auc, bac,
ber, cindex,
db, dunn, f1,
fdr, featperc,
fn, fnr, fp,
fpr, gmean,
gpr, mae, mcc,
mcp, meancosts,
measureACC, measureAUC,
measureBAC, measureFDR,
measureFN, measureFNR,
measureFP, measureFPR,
measureGMEAN, measureGPR,
measureMAE, measureMCC,
measureMEDAE, measureMEDSE,
measureMMCE, measureMSE,
measureNPV, measurePPV,
measureRMSE, measureSAE,
measureSSE, measureTN,
measureTNR, measureTP,
measureTPR, measures,
medae, medse,
mmce, mse,
multiclass.auc, npv,
ppv, rmse, sae,
silhouette, sse,
timeboth, timepredict,
timetrain, tn,
tnr, tp, tpr;
Measure, makeMeasure;
makeCostMeasure; performance