[ https://issues.apache.org/jira/browse/SPARK-12468?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-12468: ------------------------------------ Assignee: (was: Apache Spark) > getParamMap in Pyspark ML API returns empty dictionary in example for > Documentation > ----------------------------------------------------------------------------------- > > Key: SPARK-12468 > URL: https://issues.apache.org/jira/browse/SPARK-12468 > Project: Spark > Issue Type: Bug > Components: PySpark > Affects Versions: 1.5.2 > Reporter: Zachary Brown > Priority: Minor > > The `extractParamMap()` method for a model that has been fit returns an empty > dictionary, e.g. (from the [Pyspark ML API > Documentation](http://spark.apache.org/docs/latest/ml-guide.html#example-estimator-transformer-and-param)): > ```python > from pyspark.mllib.linalg import Vectors > from pyspark.ml.classification import LogisticRegression > from pyspark.ml.param import Param, Params > # 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() > ``` -- 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