mlr (version 2.8)

aggregations: Aggregation methods.

Description

• 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.

Usage

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

Format

None

See Also

Aggregation