[SPARK-16653][ML][OPTIMIZER] update ANN convergence tolerance param default to 1e-6

## What changes were proposed in this pull request?

replace ANN convergence tolerance param default
from 1e-4 to 1e-6

so that it will be the same with other algorithms in MLLib which use LBFGS as optimizer.

## How was this patch tested?

Existing Test.

Author: WeichenXu <WeichenXu123@outlook.com>

Closes #14286 from WeichenXu123/update_ann_tol.

2 files changed, 6 insertions, 6 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifier.scala
index 76ef32aa3d..7264a99b47 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifier.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifier.scala
@@ -100,7 +100,7 @@ private[classification] trait MultilayerPerceptronParams extends PredictorParams
   @Since("2.0.0")
   final def getInitialWeights: Vector = $(initialWeights)
 
-  setDefault(maxIter -> 100, tol -> 1e-4, blockSize -> 128,
+  setDefault(maxIter -> 100, tol -> 1e-6, blockSize -> 128,
     solver -> MultilayerPerceptronClassifier.LBFGS, stepSize -> 0.03)
 }
 
@@ -190,7 +190,7 @@ class MultilayerPerceptronClassifier @Since("1.5.0") (
   /**
    * Set the convergence tolerance of iterations.
    * Smaller value will lead to higher accuracy with the cost of more iterations.
-   * Default is 1E-4.
+   * Default is 1E-6.
    *
    * @group setParam
    */
diff --git a/python/pyspark/ml/classification.py b/python/pyspark/ml/classification.py
index 613bc8cb3e..9a3c7b1596 100644
--- a/python/pyspark/ml/classification.py
+++ b/python/pyspark/ml/classification.py
@@ -1124,11 +1124,11 @@ class MultilayerPerceptronClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol,
 
     @keyword_only
     def __init__(self, featuresCol="features", labelCol="label", predictionCol="prediction",
-                 maxIter=100, tol=1e-4, seed=None, layers=None, blockSize=128, stepSize=0.03,
+                 maxIter=100, tol=1e-6, seed=None, layers=None, blockSize=128, stepSize=0.03,
                  solver="l-bfgs", initialWeights=None):
         """
         __init__(self, featuresCol="features", labelCol="label", predictionCol="prediction", \
-                 maxIter=100, tol=1e-4, seed=None, layers=None, blockSize=128, stepSize=0.03, \
+                 maxIter=100, tol=1e-6, seed=None, layers=None, blockSize=128, stepSize=0.03, \
                  solver="l-bfgs", initialWeights=None)
         """
         super(MultilayerPerceptronClassifier, self).__init__()
@@ -1141,11 +1141,11 @@ class MultilayerPerceptronClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol,
     @keyword_only
     @since("1.6.0")
     def setParams(self, featuresCol="features", labelCol="label", predictionCol="prediction",
-                  maxIter=100, tol=1e-4, seed=None, layers=None, blockSize=128, stepSize=0.03,
+                  maxIter=100, tol=1e-6, seed=None, layers=None, blockSize=128, stepSize=0.03,
                   solver="l-bfgs", initialWeights=None):
         """
         setParams(self, featuresCol="features", labelCol="label", predictionCol="prediction", \
-                  maxIter=100, tol=1e-4, seed=None, layers=None, blockSize=128, stepSize=0.03, \
+                  maxIter=100, tol=1e-6, seed=None, layers=None, blockSize=128, stepSize=0.03, \
                   solver="l-bfgs", initialWeights=None)
         Sets params for MultilayerPerceptronClassifier.
         """