Add a pipeline step for feature exploration / feature engineering

[john-waczak]

• Feature Engineering (@AdamAker BARs stuff)
• Feature Selection (via ranked feature importances and Shapely values)
• Intrinsic dimension estimation
• Explore SINDy (time series) style approaches for examining sparse polynomial combinations of features
• H2O.ai style approaches...

Consider as a hyperparameter the threshold for the number of features to include. Where we have multiple methods for estimating feature importances, take the intersection of the top $n$ features from each method.

[john-waczak]

https://docs.h2o.ai/driverless-ai/1-10-lts/docs/userguide/feature-engineering.html

[john-waczak]

Also note that SciML in julia has genetic algorithms