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From "Zachary Brown (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-12468) getParamMap in Pyspark ML API returns empty dictionary in example for Documentation
Date Mon, 21 Dec 2015 20:42:46 GMT
Zachary Brown created SPARK-12468:
-------------------------------------

             Summary: 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()
```




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