LogisticRegressionModel.toString should summarize model

Author: jiayue-zhang

mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala

@@ -1169,6 +1169,10 @@ class LogisticRegressionModel private[spark] (
    */
   @Since("1.6.0")
   override def write: MLWriter = new LogisticRegressionModel.LogisticRegressionModelWriter(this)
+
+  override def toString: String = {
+    s"${super.toString}, numClasses = $numClasses, numFeatures = $numFeatures"
+  }
 }
 
 

mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala

@@ -2594,6 +2594,12 @@ class LogisticRegressionSuite
       assert(model.getFamily === family)
     }
   }
+
+  test("toString") {
+    val model = new LogisticRegressionModel("logReg", Vectors.dense(0.1, 0.2, 0.3), 0.0)
+    val expected = "logReg, numClasses = 2, numFeatures = 3"
+    assert(model.toString === expected)
+  }
 }
 
 object LogisticRegressionSuite {

python/pyspark/ml/classification.py

@@ -237,6 +237,8 @@ class LogisticRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredicti
     True
     >>> blorModel.intercept == model2.intercept
     True
+    >>> model2._resetUid("logReg")
+    uid = logReg, numClasses = 2, numFeatures = 2
 
     .. versionadded:: 1.3.0
     """
@@ -558,6 +560,11 @@ def evaluate(self, dataset):
         java_blr_summary = self._call_java("evaluate", dataset)
         return BinaryLogisticRegressionSummary(java_blr_summary)
 
+    def __repr__(self):
+        numClasses = str(self._call_java("numClasses"))
+        numFeatures = str(self._call_java("numFeatures"))
+        return "uid = %s, numClasses = %s, numFeatures = %s" % (self.uid, numClasses, numFeatures)
+
 
 class LogisticRegressionSummary(JavaWrapper):
     """

python/pyspark/mllib/classification.py

@@ -257,6 +257,9 @@ def load(cls, sc, path):
         model.setThreshold(threshold)
         return model
 
+    def __repr__(self):
+        return self._call_java("toString")
+
 
 class LogisticRegressionWithSGD(object):
     """