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memphis-iis / datawhys-content-notebooks-python

Content for DataWhys in the form of JupyterLab notebooks (.ipynb files)
Apache License 2.0
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Notebook: Lasso #11

Closed aolney closed 4 years ago

aolney commented 4 years ago

See the spreadsheet for details

Content Programming
TS TS

Ideas/prereqs: regularization, data splits/crossvalidation, overfit, bias/variance tradeoff,

Direct link https://jupyter.olney.ai/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fmemphis-iis%2Fdatawhys-content-notebooks&subPath=Lasso.ipynb&app=lab

aolney commented 4 years ago

Email from TS:

I was looking at your final version and the solutions, I think it would be easier to teach them to us LogisticRegressionCV for this problem instead. Then, the tuning parameter selection is natural. Maybe and update for the future?

aolney commented 4 years ago

Closing with https://github.com/memphis-iis/datawhys-content-notebooks/commit/2a5efe95876e9a946bbdab4c4e79269854cdb2fc to clear the board.

But we will reopen at some point for revisions :smile_cat:

aolney commented 4 years ago

Need random seed to ensure train/test split gives the same answer across notebooks