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[SPARK-14712][ML] LogisticRegressionModel.toString should summarize model #18826

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[SPARK-14712][ML] LogisticRegressionModel.toString should summarize model #18826

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a718694
LogisticRegressionModel.toString should summarize model
jiayue-zhang Aug 3, 2017
96d9430
Merge branch 'master' into spark-14712
jiayue-zhang Jun 1, 2018
189acfb
Pyspark repr by calling toString
jiayue-zhang Jun 23, 2018
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5 changes: 5 additions & 0 deletions mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -1202,6 +1202,11 @@ class LogisticRegressionModel private[spark] (
*/
@Since("1.6.0")
override def write: MLWriter = new LogisticRegressionModel.LogisticRegressionModelWriter(this)

override def toString: String = {
s"LogisticRegressionModel: " +
s"uid = ${super.toString}, numClasses = $numClasses, numFeatures = $numFeatures"
}
}


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6 changes: 6 additions & 0 deletions mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
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Expand Up @@ -2751,6 +2751,12 @@ class LogisticRegressionSuite extends MLTest with DefaultReadWriteTest {
assert(model.getFamily === family)
}
}

test("toString") {
val model = new LogisticRegressionModel("logReg", Vectors.dense(0.1, 0.2, 0.3), 0.0)
val expected = "LogisticRegressionModel: uid = logReg, numClasses = 2, numFeatures = 3"
assert(model.toString === expected)
}
}

object LogisticRegressionSuite {
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5 changes: 5 additions & 0 deletions python/pyspark/ml/classification.py
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Expand Up @@ -239,6 +239,8 @@ class LogisticRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredicti
True
>>> blorModel.intercept == model2.intercept
True
>>> model2
LogisticRegressionModel: uid = ..., numClasses = 2, numFeatures = 2

.. versionadded:: 1.3.0
"""
Expand Down Expand Up @@ -562,6 +564,9 @@ def evaluate(self, dataset):
java_blr_summary = self._call_java("evaluate", dataset)
return BinaryLogisticRegressionSummary(java_blr_summary)

def __repr__(self):
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@holdenk holdenk Jun 22, 2018

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So my question here is why we aren't calling the Java/Scala toString method directly as we do in the mllib one and in many of the other models in regression.py for the ml one?

return self._call_java("toString")


class LogisticRegressionSummary(JavaWrapper):
"""
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3 changes: 3 additions & 0 deletions python/pyspark/mllib/classification.py
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Expand Up @@ -258,6 +258,9 @@ def load(cls, sc, path):
model.setThreshold(threshold)
return model

def __repr__(self):
return self._call_java("toString")


class LogisticRegressionWithSGD(object):
"""
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