Documentation
Minor Description
SPARK-14489 adds the ability to skip NaN predictions during ALS.transform. This can be useful in production scenarios but is particularly useful when trying to use the cross-validation classes with ALS, since in many cases the test set will have users/items that are not in the training set, leading to evaluation metrics that are all NaN and making cross-validation unusable.
Add an explanation for the coldStartStrategy param to the ALS documentation, and add example code to illustrate the usage.
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Issue Links
- depends upon
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SPARK-14489 RegressionEvaluator returns NaN for ALS in Spark ml
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- Resolved
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- links to
