aggregations: Aggregation methods.
In Najah-lshanableh/R-data-mining2: Machine Learning in R

test.mean
Mean of performance values on test sets.
test.sd
Standard deviation of performance values on test sets.
test.median
Median of performance values on test sets.
test.min
Minimum of performance values on test sets.
test.max
Maximum of performance values on test sets.
test.sum
Sum of performance values on test sets.
train.mean
Mean of performance values on training sets.
train.sd
Standard deviation of performance values on training sets.
train.median
Median of performance values on training sets.
train.min
Minimum of performance values on training sets.
train.max
Maximum of performance values on training sets.
train.sum
Sum of performance values on training sets.
b632
Aggregation for B632 bootstrap.
b632plus
Aggregation for B632+ bootstrap.
testgroup.mean
Performance values on test sets are grouped according to resampling method. The mean for every group is calculated, then the mean of those means. Mainly used for repeated CV.
test.join
Performance measure on joined test sets. This is especially useful for small sample sizes where unbalanced group sizes have a significant impact on the aggregation, especially for cross-validation test.join might make sense now. For the repeated CV, the performance is calculated on each repetition and then aggregated with the arithmetic mean.

test.mean

test.sd

test.median

test.min

test.max

test.sum

test.range

test.rmse

train.mean

train.sd

train.median

train.min

train.max

train.sum

train.range

train.rmse

b632

b632plus

testgroup.mean

test.join