24 hours left to hack...
Yaaaaaaaaaaaaaaaaaaaay!
And I've been getting a couple of the usual "I'm not winning + how do I do better" messages in a sidebar. Wanting to share equally, here is how I'm responding to those:
My suggestions given that time is limited:
Check out the videos on the tree-based models (gradient boosting + forest) in the Machine Learning using SAS Viya course that's in the SAS Skill Builder for Students. There are some helpful tips in those videos on how you can finetune your models.
Consider other goodness of fit statistics. Data scientist often prefer statistics like the misclassification rate, when it comes to predictive models.
Finally, reconsider your decision thresholds, both in the evaluation of models - and in choosing the cutoff points. The same model can produce DRASTICALLY different suggestions based upon those two items... and is a primary example of why the data scientist is still a critical part of the equation.
Go get em, Hackers!
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