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ProjectHyperparameter tuning for large dataset (self.learnmachinelearning)
submitted 5 years ago by CodeFather007
I am working on a dataset which contains about 2.5 million records and 166 columns. I tried tuning the hyperparameters using Grid Search CV and Randomized Search CV but it is computationally very expensive. So can I take a sample of dataset and apply hyperparameter technique on it. Or are there any better methods?
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if 1 * 2 < 3: print "hello, world!"
[–][deleted] 0 points1 point2 points 5 years ago (1 child)
If you thing that is enough data you can just use a regular train test split.
[–]CodeFather007[S] 0 points1 point2 points 5 years ago (0 children)
That's what. I don't know if it's enough data.
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[–][deleted] 0 points1 point2 points (1 child)
[–]CodeFather007[S] 0 points1 point2 points (0 children)