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how to cross validate between different classifier models in pyspark

i have searched for a way to do in a single run cross validation between 2 or more algorithms and parameters (i.e logisticRegression & randomForest) that works on the same pre-prossesed data. saw this scala version : How to use CrossValidator to choose between different models wonder if there is also a python version.

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