AutoML optimizations: Fewer neurons in DL grids & Stacked Ensemble metalearner improvements

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We determined via benchmarking that making these two changes improve the performance of the Stacked Ensembles in AutoML, generally. It might not be an improvement on all datasets, but on a large, diverse range of datasets, we found improvements in this combination.

• Fewer neurons in the DL grids
• Add a logit transform to the CV preds before training the Stacked Ensemble metalearner
• -Search alpha = [0.5, 1.0] for regularization in the GLM metalearner in Stacked Ensembles in AutoML. Previously, we used the default of 0.5 only, but the extra chance at trying more regularization (for cases of many models, especially bad ones found via random search), helps performance.- (this was reverted later due to a bug)

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JIRA Issue Details

Jira Issue: PUBDEV-8070
Assignee: Erin LeDell
Reporter: Erin LeDell
State: Resolved
Fix Version: 3.32.1.1
Attachments: N/A
Development PRs: Available

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Linked PRs from JIRA

#5401
#5392