from RocketChat a while ago…
I remember that post. It doesn’t help though if I understood your suggestion correctly since they won’t tell us which ones are the 304 to be isolated.
The JSON file tells you which 304 features are the old “legacy” features. You should read this again: October 2021 Updates
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Looks like two of my models on new data seem OK but can be better. The best ones so far for me are low to almost 0 proportion feature neutralized models. MMC not so hot.
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I have tried to loaded two versions of examples weekly, legacy vs mass , legacy performance is better.
Thanks, I missed that communication.
It seems that some new targets are indeed better for live data. I will still wait 3-4 more weeks, then change to either a single model or an ensemble model on the new data.
How hard is the new data validation set? If I apply my old pipeline from the old dataset I get model with these stats on the new validation dataset: corr 0.01 sharpe 0.4; however, the same model trained on the old dataset manages to do 2.5x better on both stats on the old validation dataset. Is the new validation dataset significantly harder or is my pipeline not easily transferable? Do you have same experience?