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When working partitioned models in DSS, during training examples, as described at this URL
I see that the Pearson Coefficients for "all partitions" is really small in comparison to each of the subpartitions. I don't know why this would be. If they were close I'd get it. But this big a difference in values 0.19 for the All Partitions value, vs 0.90 for each independent partition seems odd.
I'm wondering if I don't know the math well enough, or if I've discovered a bug.
This problem is evident in the image in the training materials.
cc: @Alex_Reutter