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),
allowed.pred.types = character(0L), fun, extra.args = list(),
best = NULL, worst = NULL)
Measure
].Measure
,
makeMeasure
; acc
,
auc
, ber
,
cindex
, f1
,
fdr
, featperc
,
fn
, fnr
, fp
,
fpr
, gmean
,
gpr
, mae
, mcc
,
mcp
, meancosts
,
measures
, medae
,
medse
, mmce
,
mse
, multiclass.auc
,
npv
, ppv
, rmse
,
sae
, sse
,
timeboth
, timepredict
,
timetrain
, tn
,
tnr
, tp
, tpr
;
makeCostMeasure
; performance