aggregations: Aggregation methods.
Description
{
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 very 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.}Usage
test.meantest.sd
test.median
test.min
test.max
test.sum
test.range
test.sqrt.of.mean
train.mean
train.sd
train.median
train.min
train.max
train.sum
train.range
train.sqrt.of.mean
b632
b632plus
testgroup.mean
test.join