`R/aggregations.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.**testgroup.sd**

Similar to**testgroup.mean**- after the mean for every group is calculated, the standard deviation of those means is obtained. 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 testgroup.sd test.join

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