tpot
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Integration with sklearn-evaluation
I think adding an integration/tutorial and the right documentation of the framework can go a long way.
Usually, when using tpot you'd get the final model, and then you'll check performance and results. This will allow an easier mechanism for the users to solve the second part of it.
Here's a sample flow
- User creates TPOT instance
- User calls TPOT
fit()function with training data - TPOT would generate the plots for model assessment and performance evaluation. (this can also be a step 4 once the user gets the predictions).