About how to parallelize multiple Machine Learning Algorithm using a pipeline with spark.

You basically need to make a Pipeline and build a ParamGrid with different algorithms as stages.  Here is an simple example: val dt = new DecisionTreeClassifier() .setLabelCol("label") .setFeaturesCol("features") val lr = new LogisticRegression() .setLabelCol("label") .setFeaturesCol("features") val pipeline = new Pipeline() val paramGrid = new ParamGridBuilder() .addGrid(pipeline.stages, Array(Array[PipelineStage](dt), Array[PipelineStage](lr))) val cv = new CrossValidator() .setEstimator(pipeline) .setEstimatorParamMaps(paramGrid)…

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