I'm using CrossValidator and paramgrid to find the best parameters of my model. After crossvalidate, I got a CrossValidatorModel but when I want to get the parameters of my pipeline, there's nothing in the parameter list of bestmodel.
Here's the code runing on jupyter notebook: sq=SQLContext(sc) df=sq.createDataFrame([(1,0,1),(2,0,2),(1,0,1),(2,1,2),(1,1,1),(2,1,2),(3,1,1),(2,1,2),(1,1,2)],["a","b","c"]) lableIndexer=StringIndexer(inputCol="c",outputCol="label").fit(df) vecAssembler=VectorAssembler(inputCols=["a","b"],outputCol="featureVector") lr=LogisticRegression(featuresCol="featureVector",labelCol="label") pip=Pipeline() pip.setStages([lableIndexer,vecAssembler,lr]) grid=ParamGridBuilder().addGrid(lr.maxIter,[10,20,30,40]).build() evaluator=MulticlassClassificationEvaluator() cv=CrossValidator(estimator=pip,estimatorParamMaps=grid,evaluator=evaluator,numFolds=3) cvModel=cv.fit(df) cvPrediction=cvModel.transform(df) cvPrediction 0.666666 cvModel.bestModel.params [] There's no error, so what's wrong? -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/How-to-get-the-parameters-of-bestmodel-while-using-paramgrid-and-crossvalidator-tp27497.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org