[ https://issues.apache.org/jira/browse/SPARK-13368?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15557239#comment-15557239 ]
holdenk commented on SPARK-13368: --------------------------------- It seems that we don't have this in the example anymore, although https://issues.apache.org/jira/browse/SPARK-10931 / https://github.com/apache/spark/pull/14653 are working on this. > PySpark JavaModel fails to extract params from Spark side automatically > ----------------------------------------------------------------------- > > Key: SPARK-13368 > URL: https://issues.apache.org/jira/browse/SPARK-13368 > Project: Spark > Issue Type: Bug > Components: PySpark > Reporter: Xusen Yin > Priority: Minor > > JavaModel fails to extract params from Spark side automatically that causes > model.extractParamMap() is always empty. As shown in the example code below > copied from Spark Guide > https://spark.apache.org/docs/latest/ml-guide.html#example-estimator-transformer-and-param > {code} > # Prepare training data from a list of (label, features) tuples. > training = sqlContext.createDataFrame([ > (1.0, Vectors.dense([0.0, 1.1, 0.1])), > (0.0, Vectors.dense([2.0, 1.0, -1.0])), > (0.0, Vectors.dense([2.0, 1.3, 1.0])), > (1.0, Vectors.dense([0.0, 1.2, -0.5]))], ["label", "features"]) > # Create a LogisticRegression instance. This instance is an Estimator. > lr = LogisticRegression(maxIter=10, regParam=0.01) > # Print out the parameters, documentation, and any default values. > print "LogisticRegression parameters:\n" + lr.explainParams() + "\n" > # Learn a LogisticRegression model. This uses the parameters stored in lr. > model1 = lr.fit(training) > # Since model1 is a Model (i.e., a transformer produced by an Estimator), > # we can view the parameters it used during fit(). > # This prints the parameter (name: value) pairs, where names are unique > # IDs for this LogisticRegression instance. > print "Model 1 was fit using parameters: " > print model1.extractParamMap() > {code} > The result of model1.extractParamMap() is {}. > Question is, should we provide the feature or not? If yes, we need either let > Model share same params with Estimator or adds a parent in Model and points > to its Estimator; if not, we should remove those lines from example code. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org