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It's an ultra high resolution sales forecast model for a national retailer. It's made somewhat more manageable by the fact that the data is 1D instead of 2D th
by chroem- 6y ago
It's an ultra high resolution sales forecast model for a national retailer. It's made somewhat more manageable by the fact that the data is 1D instead of 2D though.
- gwern 6y agoI wonder if that's an important difference? Sales data seems far more noisy and less informative than all of the scaling research datasets I can think of like images or text. It could also just be that you had some minor flaw causing underfitting in your approach like using too-small models which aren't compute-optimal or too much regularization (a critical part of scaling papers is removing standard regularizers like dropout to avoid hobbling the model).
- chroem- 6y agoI've found that it's surprisingly insensitive to the amount of regularization applied, however it definitely does warrant further experimentation. Also, I expect that one other distinction vs. image data is much higher correlation between samples in the dataset.