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For repeated-CV, the test.join currently computes the measure for each repeated cv separately and then averages this through the mean. For example, a 3 times repeated 10-fold CV creates cross-validated predictions for each repetition, e.g. y1, y2, and y3. In this case, currently test.join computes the measure for y1 and the real y, y2 and the real y, y3 and the real y and finally aggregates the three values using the mean. (why aggregating here? especially why using the mean?).
An alternative to this (without the issue of aggregating) would be to average the cross-validated predictions accross all reps, i.e., use the mean ymean = (y1+y2+y3)/3 and compute the measure using ymean and the real y.
I observed this issue while doing #1275.
@giuseppec said:
@larskotthoff said:
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