diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala
index 2d0212f36f..e021093753 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala
@@ -237,7 +237,8 @@ class DecisionTreeClassificationModel private[ml] (
 
   @Since("1.4.0")
   override def toString: String = {
-    s"DecisionTreeClassificationModel (uid=$uid) of depth $depth with $numNodes nodes"
+    s"DecisionTreeClassificationModel: uid=$uid, depth=$depth, numNodes=$numNodes, " +
+      s"numClasses=$numClasses, numFeatures=$numFeatures"
   }
 
   /**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala
index 5bc45f2b02..e1f5338f34 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala
@@ -340,7 +340,8 @@ class GBTClassificationModel private[ml](
 
   @Since("1.4.0")
   override def toString: String = {
-    s"GBTClassificationModel (uid=$uid) with $numTrees trees"
+    s"GBTClassificationModel: uid = $uid, numTrees=$numTrees, numClasses=$numClasses, " +
+      s"numFeatures=$numFeatures"
   }
 
   /**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LinearSVC.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LinearSVC.scala
index 0dc1c24570..45114f6ee8 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/LinearSVC.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/LinearSVC.scala
@@ -326,6 +326,10 @@ class LinearSVCModel private[classification] (
   @Since("2.2.0")
   override def write: MLWriter = new LinearSVCModel.LinearSVCWriter(this)
 
+  @Since("3.0.0")
+  override def toString: String = {
+    s"LinearSVCModel: uid=$uid, numClasses=$numClasses, numFeatures=$numFeatures"
+  }
 }
 
 
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
index 1d1d139ba0..1cb5915239 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
@@ -1181,8 +1181,7 @@ class LogisticRegressionModel private[spark] (
   override def write: MLWriter = new LogisticRegressionModel.LogisticRegressionModelWriter(this)
 
   override def toString: String = {
-    s"LogisticRegressionModel: " +
-    s"uid = ${super.toString}, numClasses = $numClasses, numFeatures = $numFeatures"
+    s"LogisticRegressionModel: uid=$uid, numClasses=$numClasses, numFeatures=$numFeatures"
   }
 }
 
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 41db6f3f44..8c5d768044 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
@@ -323,6 +323,12 @@ class MultilayerPerceptronClassificationModel private[ml] (
   override protected def predictRaw(features: Vector): Vector = mlpModel.predictRaw(features)
 
   override def numClasses: Int = layers.last
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"MultilayerPerceptronClassificationModel: uid=$uid, numLayers=${layers.length}, " +
+      s"numClasses=$numClasses, numFeatures=$numFeatures"
+  }
 }
 
 @Since("2.0.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala
index 205f565aa2..bcca40d159 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala
@@ -359,7 +359,8 @@ class NaiveBayesModel private[ml] (
 
   @Since("1.5.0")
   override def toString: String = {
-    s"NaiveBayesModel (uid=$uid) with ${pi.size} classes"
+    s"NaiveBayesModel: uid=$uid, modelType=${$(modelType)}, numClasses=$numClasses, " +
+      s"numFeatures=$numFeatures"
   }
 
   @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala
index 675315e3bb..51a624795c 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala
@@ -257,6 +257,12 @@ final class OneVsRestModel private[ml] (
 
   @Since("2.0.0")
   override def write: MLWriter = new OneVsRestModel.OneVsRestModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"OneVsRestModel: uid=$uid, classifier=${$(classifier)}, numClasses=$numClasses, " +
+      s"numFeatures=$numFeatures"
+  }
 }
 
 @Since("2.0.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala
index 245cda35d8..bc28d783ed 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala
@@ -260,7 +260,8 @@ class RandomForestClassificationModel private[ml] (
 
   @Since("1.4.0")
   override def toString: String = {
-    s"RandomForestClassificationModel (uid=$uid) with $getNumTrees trees"
+    s"RandomForestClassificationModel: uid=$uid, numTrees=$getNumTrees, numClasses=$numClasses, " +
+      s"numFeatures=$numFeatures"
   }
 
   /**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala b/mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala
index 4ad0cb55b0..5f2316fa7c 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala
@@ -91,6 +91,9 @@ class BisectingKMeansModel private[ml] (
   extends Model[BisectingKMeansModel] with BisectingKMeansParams with MLWritable
   with HasTrainingSummary[BisectingKMeansSummary] {
 
+  @Since("3.0.0")
+  lazy val numFeatures: Int = parentModel.clusterCenters.head.size
+
   @Since("2.0.0")
   override def copy(extra: ParamMap): BisectingKMeansModel = {
     val copied = copyValues(new BisectingKMeansModel(uid, parentModel), extra)
@@ -145,6 +148,12 @@ class BisectingKMeansModel private[ml] (
   @Since("2.0.0")
   override def write: MLWriter = new BisectingKMeansModel.BisectingKMeansModelWriter(this)
 
+  @Since("3.0.0")
+  override def toString: String = {
+    s"BisectingKMeansModel: uid=$uid, k=${parentModel.k}, distanceMeasure=${$(distanceMeasure)}, " +
+      s"numFeatures=$numFeatures"
+  }
+
   /**
    * Gets summary of model on training set. An exception is
    * thrown if `hasSummary` is false.
diff --git a/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala b/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala
index b4d9a9f882..916f326ab5 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala
@@ -89,6 +89,9 @@ class GaussianMixtureModel private[ml] (
   extends Model[GaussianMixtureModel] with GaussianMixtureParams with MLWritable
   with HasTrainingSummary[GaussianMixtureSummary] {
 
+  @Since("3.0.0")
+  lazy val numFeatures: Int = gaussians.head.mean.size
+
   /** @group setParam */
   @Since("2.1.0")
   def setFeaturesCol(value: String): this.type = set(featuresCol, value)
@@ -186,6 +189,11 @@ class GaussianMixtureModel private[ml] (
   @Since("2.0.0")
   override def write: MLWriter = new GaussianMixtureModel.GaussianMixtureModelWriter(this)
 
+  @Since("3.0.0")
+  override def toString: String = {
+    s"GaussianMixtureModel: uid=$uid, k=${weights.length}, numFeatures=$numFeatures"
+  }
+
   /**
    * Gets summary of model on training set. An exception is
    * thrown if `hasSummary` is false.
diff --git a/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala b/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala
index 5cc0f38c67..caeded400f 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala
@@ -108,6 +108,9 @@ class KMeansModel private[ml] (
   extends Model[KMeansModel] with KMeansParams with GeneralMLWritable
     with HasTrainingSummary[KMeansSummary] {
 
+  @Since("3.0.0")
+  lazy val numFeatures: Int = parentModel.clusterCenters.head.size
+
   @Since("1.5.0")
   override def copy(extra: ParamMap): KMeansModel = {
     val copied = copyValues(new KMeansModel(uid, parentModel), extra)
@@ -153,6 +156,12 @@ class KMeansModel private[ml] (
   @Since("1.6.0")
   override def write: GeneralMLWriter = new GeneralMLWriter(this)
 
+  @Since("3.0.0")
+  override def toString: String = {
+    s"KMeansModel: uid=$uid, k=${parentModel.k}, distanceMeasure=${$(distanceMeasure)}, " +
+      s"numFeatures=$numFeatures"
+  }
+
   /**
    * Gets summary of model on training set. An exception is
    * thrown if `hasSummary` is false.
diff --git a/mllib/src/main/scala/org/apache/spark/ml/clustering/LDA.scala b/mllib/src/main/scala/org/apache/spark/ml/clustering/LDA.scala
index 91201e7bd0..9b0005b374 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/clustering/LDA.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/clustering/LDA.scala
@@ -620,6 +620,11 @@ class LocalLDAModel private[ml] (
 
   @Since("1.6.0")
   override def write: MLWriter = new LocalLDAModel.LocalLDAModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"LocalLDAModel: uid=$uid, k=${$(k)}, numFeatures=$vocabSize"
+  }
 }
 
 
@@ -783,6 +788,11 @@ class DistributedLDAModel private[ml] (
 
   @Since("1.6.0")
   override def write: MLWriter = new DistributedLDAModel.DistributedWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"DistributedLDAModel: uid=$uid, k=${$(k)}, numFeatures=$vocabSize"
+  }
 }
 
 
diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
index 09e8e7b232..55b910e98d 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
@@ -130,6 +130,12 @@ class BinaryClassificationEvaluator @Since("1.4.0") (@Since("1.4.0") override va
 
   @Since("1.4.1")
   override def copy(extra: ParamMap): BinaryClassificationEvaluator = defaultCopy(extra)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"BinaryClassificationEvaluator: uid=$uid, metricName=${$(metricName)}, " +
+      s"numBins=${$(numBins)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/ClusteringEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/ClusteringEvaluator.scala
index 868bd2a763..157bed2a6b 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/ClusteringEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/ClusteringEvaluator.scala
@@ -120,6 +120,12 @@ class ClusteringEvaluator @Since("2.3.0") (@Since("2.3.0") override val uid: Str
         throw new IllegalArgumentException(s"No support for metric $mn, distance $dm")
     }
   }
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"ClusteringEvaluator: uid=$uid, metricName=${$(metricName)}, " +
+      s"distanceMeasure=${$(distanceMeasure)}"
+  }
 }
 
 
diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala
index bac3e23774..ab14227f06 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala
@@ -184,6 +184,12 @@ class MulticlassClassificationEvaluator @Since("1.5.0") (@Since("1.5.0") overrid
 
   @Since("1.5.0")
   override def copy(extra: ParamMap): MulticlassClassificationEvaluator = defaultCopy(extra)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"MulticlassClassificationEvaluator: uid=$uid, metricName=${$(metricName)}, " +
+      s"metricLabel=${$(metricLabel)}, beta=${$(beta)}, eps=${$(eps)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/MultilabelClassificationEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/MultilabelClassificationEvaluator.scala
index f12c6700be..5216c40819 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/MultilabelClassificationEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/MultilabelClassificationEvaluator.scala
@@ -121,6 +121,12 @@ class MultilabelClassificationEvaluator (override val uid: String)
   }
 
   override def copy(extra: ParamMap): MultilabelClassificationEvaluator = defaultCopy(extra)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"MultilabelClassificationEvaluator: uid=$uid, metricName=${$(metricName)}, " +
+      s"metricLabel=${$(metricLabel)}"
+  }
 }
 
 
diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/RankingEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/RankingEvaluator.scala
index 64ab3c3f7f..ca3a8ebc16 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/RankingEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/RankingEvaluator.scala
@@ -105,6 +105,11 @@ class RankingEvaluator (override val uid: String)
   override def isLargerBetter: Boolean = true
 
   override def copy(extra: ParamMap): RankingEvaluator = defaultCopy(extra)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"RankingEvaluator: uid=$uid, metricName=${$(metricName)}, k=${$(k)}"
+  }
 }
 
 
diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala
index b0cafefe42..9f32d40d16 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala
@@ -124,6 +124,12 @@ final class RegressionEvaluator @Since("1.4.0") (@Since("1.4.0") override val ui
 
   @Since("1.5.0")
   override def copy(extra: ParamMap): RegressionEvaluator = defaultCopy(extra)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"RegressionEvaluator: uid=$uid, metricName=${$(metricName)}, " +
+      s"throughOrigin=${$(throughOrigin)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Binarizer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Binarizer.scala
index ec4d45b653..07a4f91443 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/Binarizer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Binarizer.scala
@@ -204,6 +204,13 @@ final class Binarizer @Since("1.4.0") (@Since("1.4.0") override val uid: String)
 
   @Since("1.4.1")
   override def copy(extra: ParamMap): Binarizer = defaultCopy(extra)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"Binarizer: uid=$uid" +
+      get(inputCols).map(c => s", numInputCols=${c.length}").getOrElse("") +
+      get(outputCols).map(c => s", numOutputCols=${c.length}").getOrElse("")
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSH.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSH.scala
index c074830ec9..4e266fbc1e 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSH.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSH.scala
@@ -106,6 +106,11 @@ class BucketedRandomProjectionLSHModel private[ml](
   override def write: MLWriter = {
     new BucketedRandomProjectionLSHModel.BucketedRandomProjectionLSHModelWriter(this)
   }
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"BucketedRandomProjectionLSHModel: uid=$uid, numHashTables=${$(numHashTables)}"
+  }
 }
 
 /**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Bucketizer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Bucketizer.scala
index 8533ed5ce5..9aeddae78e 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/Bucketizer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Bucketizer.scala
@@ -215,6 +215,13 @@ final class Bucketizer @Since("1.4.0") (@Since("1.4.0") override val uid: String
   override def copy(extra: ParamMap): Bucketizer = {
     defaultCopy[Bucketizer](extra).setParent(parent)
   }
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"Bucketizer: uid=$uid" +
+      get(inputCols).map(c => s", numInputCols=${c.length}").getOrElse("") +
+      get(outputCols).map(c => s", numOutputCols=${c.length}").getOrElse("")
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/ChiSqSelector.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/ChiSqSelector.scala
index 2a3656c495..9103e4feac 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/ChiSqSelector.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/ChiSqSelector.scala
@@ -316,6 +316,11 @@ final class ChiSqSelectorModel private[ml] (
 
   @Since("1.6.0")
   override def write: MLWriter = new ChiSqSelectorModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"ChiSqSelectorModel: uid=$uid, numSelectedFeatures=${selectedFeatures.length}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala
index e78e6d4f76..c58d44d492 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala
@@ -307,7 +307,7 @@ class CountVectorizerModel(
     }
     val dictBr = broadcastDict.get
     val minTf = $(minTF)
-    val vectorizer = udf { (document: Seq[String]) =>
+    val vectorizer = udf { document: Seq[String] =>
       val termCounts = new OpenHashMap[Int, Double]
       var tokenCount = 0L
       document.foreach { term =>
@@ -344,6 +344,11 @@ class CountVectorizerModel(
 
   @Since("1.6.0")
   override def write: MLWriter = new CountVectorizerModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"CountVectorizerModel: uid=$uid, vocabularySize=${vocabulary.length}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/DCT.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/DCT.scala
index 84d6a536cc..e2167f0128 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/DCT.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/DCT.scala
@@ -74,6 +74,11 @@ class DCT @Since("1.5.0") (@Since("1.5.0") override val uid: String)
   }
 
   override protected def outputDataType: DataType = new VectorUDT
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"DCT: uid=$uid, inverse=$inverse"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala
index 2f32923543..227c13d60f 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala
@@ -81,6 +81,12 @@ class ElementwiseProduct @Since("1.4.0") (@Since("1.4.0") override val uid: Stri
   }
 
   override protected def outputDataType: DataType = new VectorUDT()
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"ElementwiseProduct: uid=$uid" +
+      get(scalingVec).map(v => s", vectorSize=${v.size}").getOrElse("")
+  }
 }
 
 @Since("2.0.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/FeatureHasher.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/FeatureHasher.scala
index 61b4d5d54a..39862554c5 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/FeatureHasher.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/FeatureHasher.scala
@@ -22,7 +22,7 @@ import org.apache.spark.annotation.Since
 import org.apache.spark.ml.Transformer
 import org.apache.spark.ml.attribute.AttributeGroup
 import org.apache.spark.ml.linalg.Vectors
-import org.apache.spark.ml.param.{IntParam, ParamMap, ParamValidators, StringArrayParam}
+import org.apache.spark.ml.param.{ParamMap, StringArrayParam}
 import org.apache.spark.ml.param.shared.{HasInputCols, HasNumFeatures, HasOutputCol}
 import org.apache.spark.ml.util.{DefaultParamsReadable, DefaultParamsWritable, Identifiable, SchemaUtils}
 import org.apache.spark.mllib.feature.{HashingTF => OldHashingTF}
@@ -199,6 +199,13 @@ class FeatureHasher(@Since("2.3.0") override val uid: String) extends Transforme
     val attrGroup = new AttributeGroup($(outputCol), $(numFeatures))
     SchemaUtils.appendColumn(schema, attrGroup.toStructField())
   }
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"FeatureHasher: uid=$uid, numFeatures=${$(numFeatures)}" +
+      get(inputCols).map(c => s", numInputCols=${c.length}").getOrElse("") +
+      get(categoricalCols).map(c => s", numCategoricalCols=${c.length}").getOrElse("")
+  }
 }
 
 @Since("2.3.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala
index fe9f4f2123..80bf85936a 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala
@@ -127,6 +127,11 @@ class HashingTF @Since("1.4.0") (@Since("1.4.0") override val uid: String)
 
   @Since("1.4.1")
   override def copy(extra: ParamMap): HashingTF = defaultCopy(extra)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"HashingTF: uid=$uid, binary=${$(binary)}, numFeatures=${$(numFeatures)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/IDF.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/IDF.scala
index 4338421bf8..5f4103abcf 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/IDF.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/IDF.scala
@@ -175,9 +175,13 @@ class IDFModel private[ml] (
   @Since("3.0.0")
   def numDocs: Long = idfModel.numDocs
 
-
   @Since("1.6.0")
   override def write: MLWriter = new IDFModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"IDFModel: uid=$uid, numDocs=$numDocs"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Imputer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Imputer.scala
index fbccfb1041..64f1722f5f 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/Imputer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Imputer.scala
@@ -274,6 +274,13 @@ class ImputerModel private[ml] (
 
   @Since("2.2.0")
   override def write: MLWriter = new ImputerModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"ImputerModel: uid=$uid, strategy=${$(strategy)}, missingValue=${$(missingValue)}" +
+      get(inputCols).map(c => s", numInputCols=${c.length}").getOrElse("") +
+      get(outputCols).map(c => s", numOutputCols=${c.length}").getOrElse("")
+  }
 }
 
 
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Interaction.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Interaction.scala
index 611f1b691b..9a4f1d97c9 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/Interaction.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Interaction.scala
@@ -218,6 +218,11 @@ class Interaction @Since("1.6.0") (@Since("1.6.0") override val uid: String) ext
   @Since("1.6.0")
   override def copy(extra: ParamMap): Interaction = defaultCopy(extra)
 
+  @Since("3.0.0")
+  override def toString: String = {
+    s"Interaction: uid=$uid" +
+      get(inputCols).map(c => s", numInputCols=${c.length}").getOrElse("")
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/MaxAbsScaler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/MaxAbsScaler.scala
index 88d09d760b..6bab70e502 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/MaxAbsScaler.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/MaxAbsScaler.scala
@@ -140,6 +140,11 @@ class MaxAbsScalerModel private[ml] (
 
   @Since("1.6.0")
   override def write: MLWriter = new MaxAbsScalerModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"MaxAbsScalerModel: uid=$uid, numFeatures=${maxAbs.size}"
+  }
 }
 
 @Since("2.0.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/MinHashLSH.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/MinHashLSH.scala
index da0eaad667..de7fe91c41 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/MinHashLSH.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/MinHashLSH.scala
@@ -96,6 +96,11 @@ class MinHashLSHModel private[ml](
 
   @Since("2.1.0")
   override def write: MLWriter = new MinHashLSHModel.MinHashLSHModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"MinHashLSHModel: uid=$uid, numHashTables=${$(numHashTables)}"
+  }
 }
 
 /**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/MinMaxScaler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/MinMaxScaler.scala
index b0d7b637ca..e381a0435e 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/MinMaxScaler.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/MinMaxScaler.scala
@@ -226,6 +226,12 @@ class MinMaxScalerModel private[ml] (
 
   @Since("1.6.0")
   override def write: MLWriter = new MinMaxScalerModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"MinMaxScalerModel: uid=$uid, numFeatures=${originalMin.size}, min=${$(min)}, " +
+      s"max=${$(max)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/NGram.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/NGram.scala
index e0772d5af2..fd6fde0744 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/NGram.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/NGram.scala
@@ -70,6 +70,11 @@ class NGram @Since("1.5.0") (@Since("1.5.0") override val uid: String)
   }
 
   override protected def outputDataType: DataType = new ArrayType(StringType, false)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"NGram: uid=$uid, n=${$(n)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Normalizer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Normalizer.scala
index 5db7f5da49..d129c2b2c2 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/Normalizer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Normalizer.scala
@@ -65,6 +65,11 @@ class Normalizer @Since("1.4.0") (@Since("1.4.0") override val uid: String)
   }
 
   override protected def outputDataType: DataType = new VectorUDT()
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"Normalizer: uid=$uid, p=${$(p)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/OneHotEncoder.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/OneHotEncoder.scala
index 459994c352..fd58043cda 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/OneHotEncoder.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/OneHotEncoder.scala
@@ -376,6 +376,13 @@ class OneHotEncoderModel private[ml] (
 
   @Since("3.0.0")
   override def write: MLWriter = new OneHotEncoderModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"OneHotEncoderModel: uid=$uid, dropLast=${$(dropLast)}, handleInvalid=${$(handleInvalid)}" +
+      get(inputCols).map(c => s", numInputCols=${c.length}").getOrElse("") +
+      get(outputCols).map(c => s", numOutputCols=${c.length}").getOrElse("")
+  }
 }
 
 @Since("3.0.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/PCA.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/PCA.scala
index aa5a171d4f..69dcacbb0c 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/PCA.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/PCA.scala
@@ -179,6 +179,11 @@ class PCAModel private[ml] (
 
   @Since("1.6.0")
   override def write: MLWriter = new PCAModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"PCAModel: uid=$uid, k=${$(k)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/PolynomialExpansion.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/PolynomialExpansion.scala
index 5734b06ee9..592ca001a2 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/PolynomialExpansion.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/PolynomialExpansion.scala
@@ -77,6 +77,11 @@ class PolynomialExpansion @Since("1.4.0") (@Since("1.4.0") override val uid: Str
 
   @Since("1.4.1")
   override def copy(extra: ParamMap): PolynomialExpansion = defaultCopy(extra)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"PolynomialExpansion: uid=$uid, degree=${$(degree)}"
+  }
 }
 
 /**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
index 9e95762f12..7ccfafa4ac 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
@@ -320,7 +320,10 @@ class RFormula @Since("1.5.0") (@Since("1.5.0") override val uid: String)
   override def copy(extra: ParamMap): RFormula = defaultCopy(extra)
 
   @Since("2.0.0")
-  override def toString: String = s"RFormula(${get(formula).getOrElse("")}) (uid=$uid)"
+  override def toString: String = {
+    s"RFormula: uid=$uid" +
+      get(formula).map(f => s", formula = $f").getOrElse("")
+  }
 }
 
 @Since("2.0.0")
@@ -376,7 +379,9 @@ class RFormulaModel private[feature](
   }
 
   @Since("2.0.0")
-  override def toString: String = s"RFormulaModel($resolvedFormula) (uid=$uid)"
+  override def toString: String = {
+    s"RFormulaModel: uid=$uid, resolvedFormula=$resolvedFormula"
+  }
 
   private def transformLabel(dataset: Dataset[_]): DataFrame = {
     val labelName = resolvedFormula.label
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/RobustScaler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/RobustScaler.scala
index 1d609ef319..1b9b808293 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/RobustScaler.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/RobustScaler.scala
@@ -251,6 +251,12 @@ class RobustScalerModel private[ml] (
   }
 
   override def write: MLWriter = new RobustScalerModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"RobustScalerModel: uid=$uid, numFeatures=${median.size}, " +
+      s"withCentering=${$(withCentering)}, withScaling=${$(withScaling)}"
+  }
 }
 
 @Since("3.0.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/SQLTransformer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/SQLTransformer.scala
index 0fb1d8c5dc..9b99b8177a 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/SQLTransformer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/SQLTransformer.scala
@@ -90,6 +90,11 @@ class SQLTransformer @Since("1.6.0") (@Since("1.6.0") override val uid: String)
 
   @Since("1.6.0")
   override def copy(extra: ParamMap): SQLTransformer = defaultCopy(extra)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"SQLTransformer: uid=$uid, statement=${$(statement)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala
index 834c21e16d..41e319c1fb 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala
@@ -184,6 +184,12 @@ class StandardScalerModel private[ml] (
 
   @Since("1.6.0")
   override def write: MLWriter = new StandardScalerModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"StandardScalerModel: uid=$uid, numFeatures=${mean.size}, withMean=${$(withMean)}, " +
+      s"withStd=${$(withStd)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/StopWordsRemover.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/StopWordsRemover.scala
index f95e03ae6c..57fe7c9c0a 100755
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/StopWordsRemover.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/StopWordsRemover.scala
@@ -156,6 +156,12 @@ class StopWordsRemover @Since("1.5.0") (@Since("1.5.0") override val uid: String
 
   @Since("1.5.0")
   override def copy(extra: ParamMap): StopWordsRemover = defaultCopy(extra)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"StopWordsRemover: uid=$uid, numStopWords=${$(stopWords).length}, locale=${$(locale)}, " +
+      s"caseSensitive=${$(caseSensitive)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
index 2ce5acf1fe..9f9f097a26 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
@@ -412,7 +412,7 @@ class StringIndexerModel (
   override def transform(dataset: Dataset[_]): DataFrame = {
     transformSchema(dataset.schema, logging = true)
 
-    var (inputColNames, outputColNames) = getInOutCols()
+    val (inputColNames, outputColNames) = getInOutCols()
     val outputColumns = new Array[Column](outputColNames.length)
 
     // Skips invalid rows if `handleInvalid` is set to `StringIndexer.SKIP_INVALID`.
@@ -473,6 +473,14 @@ class StringIndexerModel (
 
   @Since("1.6.0")
   override def write: StringIndexModelWriter = new StringIndexModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"StringIndexerModel: uid=$uid, handleInvalid=${$(handleInvalid)}" +
+      get(stringOrderType).map(t => s", stringOrderType=$t").getOrElse("") +
+      get(inputCols).map(c => s", numInputCols=${c.length}").getOrElse("") +
+      get(outputCols).map(c => s", numOutputCols=${c.length}").getOrElse("")
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala
index e6e9bdfd29..5ec5b77325 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala
@@ -175,6 +175,12 @@ class VectorAssembler @Since("1.4.0") (@Since("1.4.0") override val uid: String)
 
   @Since("1.4.1")
   override def copy(extra: ParamMap): VectorAssembler = defaultCopy(extra)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"VectorAssembler: uid=$uid, handleInvalid=${$(handleInvalid)}" +
+      get(inputCols).map(c => s", numInputCols=${c.length}").getOrElse("")
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala
index 6a3305aad8..18a82e5fe9 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala
@@ -428,7 +428,7 @@ class VectorIndexerModel private[ml] (
   override def transform(dataset: Dataset[_]): DataFrame = {
     transformSchema(dataset.schema, logging = true)
     val newField = prepOutputField(dataset.schema)
-    val transformUDF = udf { (vector: Vector) => transformFunc(vector) }
+    val transformUDF = udf { vector: Vector => transformFunc(vector) }
     val newCol = transformUDF(dataset($(inputCol)))
     val ds = dataset.withColumn($(outputCol), newCol, newField.metadata)
     if (getHandleInvalid == VectorIndexer.SKIP_INVALID) {
@@ -506,6 +506,11 @@ class VectorIndexerModel private[ml] (
 
   @Since("1.6.0")
   override def write: MLWriter = new VectorIndexerModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"VectorIndexerModel: uid=$uid, numFeatures=$numFeatures, handleInvalid=${$(handleInvalid)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorSizeHint.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorSizeHint.scala
index 5d787f263a..0f778e09a8 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorSizeHint.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorSizeHint.scala
@@ -176,6 +176,11 @@ class VectorSizeHint @Since("2.3.0") (@Since("2.3.0") override val uid: String)
 
   @Since("2.3.0")
   override def copy(extra: ParamMap): this.type = defaultCopy(extra)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"VectorSizeHint: uid=$uid, size=${$(size)}, handleInvalid=${$(handleInvalid)}"
+  }
 }
 
 @Since("2.3.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorSlicer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorSlicer.scala
index e3e462d07e..b84b8af4e8 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorSlicer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorSlicer.scala
@@ -159,6 +159,12 @@ final class VectorSlicer @Since("1.5.0") (@Since("1.5.0") override val uid: Stri
 
   @Since("1.5.0")
   override def copy(extra: ParamMap): VectorSlicer = defaultCopy(extra)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"VectorSlicer: uid=$uid" +
+      get(indices).map(i => s", numSelectedFeatures=${i.length}").getOrElse("")
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Word2Vec.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Word2Vec.scala
index 6ae90b8050..81dde0315c 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/Word2Vec.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Word2Vec.scala
@@ -324,6 +324,12 @@ class Word2VecModel private[ml] (
 
   @Since("1.6.0")
   override def write: MLWriter = new Word2VecModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"Word2VecModel: uid=$uid, numWords=${wordVectors.wordIndex.size}, " +
+      s"vectorSize=${$(vectorSize)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala b/mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala
index e1c9b927a2..a9592dbfca 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala
@@ -310,6 +310,11 @@ class FPGrowthModel private[ml] (
 
   @Since("2.2.0")
   override def write: MLWriter = new FPGrowthModel.FPGrowthModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"FPGrowthModel: uid=$uid, numTrainingRecords=$numTrainingRecords"
+  }
 }
 
 @Since("2.2.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
index 5049ef9245..e72d7cab00 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
@@ -338,6 +338,11 @@ class ALSModel private[ml] (
   @Since("1.6.0")
   override def write: MLWriter = new ALSModel.ALSModelWriter(this)
 
+  @Since("3.0.0")
+  override def toString: String = {
+    s"ALSModel: uid=$uid, rank=$rank"
+  }
+
   /**
    * Returns top `numItems` items recommended for each user, for all users.
    * @param numItems max number of recommendations for each user
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala
index 1ce5b5b02b..fe89aed9a9 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala
@@ -311,6 +311,9 @@ class AFTSurvivalRegressionModel private[ml] (
     @Since("1.6.0") val scale: Double)
   extends Model[AFTSurvivalRegressionModel] with AFTSurvivalRegressionParams with MLWritable {
 
+  @Since("3.0.0")
+  lazy val numFeatures: Int = coefficients.size
+
   /** @group setParam */
   @Since("1.6.0")
   def setFeaturesCol(value: String): this.type = set(featuresCol, value)
@@ -386,6 +389,11 @@ class AFTSurvivalRegressionModel private[ml] (
   @Since("1.6.0")
   override def write: MLWriter =
     new AFTSurvivalRegressionModel.AFTSurvivalRegressionModelWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"AFTSurvivalRegressionModel: uid=$uid, numFeatures=$numFeatures"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala
index 05851d5116..4a97997a1d 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala
@@ -243,7 +243,8 @@ class DecisionTreeRegressionModel private[ml] (
 
   @Since("1.4.0")
   override def toString: String = {
-    s"DecisionTreeRegressionModel (uid=$uid) of depth $depth with $numNodes nodes"
+    s"DecisionTreeRegressionModel: uid=$uid, depth=$depth, numNodes=$numNodes, " +
+      s"numFeatures=$numFeatures"
   }
 
   /**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala
index 9c38647642..700f7a2075 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala
@@ -302,7 +302,7 @@ class GBTRegressionModel private[ml](
 
   @Since("1.4.0")
   override def toString: String = {
-    s"GBTRegressionModel (uid=$uid) with $numTrees trees"
+    s"GBTRegressionModel: uid=$uid, numTrees=$numTrees, numFeatures=$numFeatures"
   }
 
   /**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
index c504a54629..53b29102f0 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
@@ -1106,6 +1106,12 @@ class GeneralizedLinearRegressionModel private[ml] (
     new GeneralizedLinearRegressionModel.GeneralizedLinearRegressionModelWriter(this)
 
   override val numFeatures: Int = coefficients.size
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"GeneralizedLinearRegressionModel: uid=$uid, family=${$(family)}, link=${$(link)}, " +
+      s"numFeatures=$numFeatures"
+  }
 }
 
 @Since("2.0.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/IsotonicRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/IsotonicRegression.scala
index 8b9233dcdc..47f9e4bfb8 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/IsotonicRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/IsotonicRegression.scala
@@ -259,6 +259,14 @@ class IsotonicRegressionModel private[ml] (
   @Since("1.6.0")
   override def write: MLWriter =
     new IsotonicRegressionModelWriter(this)
+
+  @Since("3.0.0")
+  val numFeatures: Int = 1
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"IsotonicRegressionModel: uid=$uid, numFeatures=$numFeatures"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
index 25c6f4d980..dad1080cea 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
@@ -702,6 +702,11 @@ class LinearRegressionModel private[ml] (
    */
   @Since("1.6.0")
   override def write: GeneralMLWriter = new GeneralMLWriter(this)
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"LinearRegressionModel: uid=$uid, numFeatures=$numFeatures"
+  }
 }
 
 /** A writer for LinearRegression that handles the "internal" (or default) format */
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala
index 8f78fc1da1..c3afab57a4 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala
@@ -235,7 +235,7 @@ class RandomForestRegressionModel private[ml] (
 
   @Since("1.4.0")
   override def toString: String = {
-    s"RandomForestRegressionModel (uid=$uid) with $getNumTrees trees"
+    s"RandomForestRegressionModel: uid=$uid, numTrees=$getNumTrees, numFeatures=$numFeatures"
   }
 
   /**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala b/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala
index e60a14f976..fff18bcbec 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala
@@ -323,6 +323,11 @@ class CrossValidatorModel private[ml] (
   override def write: CrossValidatorModel.CrossValidatorModelWriter = {
     new CrossValidatorModel.CrossValidatorModelWriter(this)
   }
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"CrossValidatorModel: uid=$uid, bestModel=$bestModel, numFolds=${$(numFolds)}"
+  }
 }
 
 @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala b/mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala
index 8b251197af..ecf9b846ee 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala
@@ -140,7 +140,7 @@ class TrainValidationSplit @Since("1.5.0") (@Since("1.5.0") override val uid: St
 
     val collectSubModelsParam = $(collectSubModels)
 
-    var subModels: Option[Array[Model[_]]] = if (collectSubModelsParam) {
+    val subModels: Option[Array[Model[_]]] = if (collectSubModelsParam) {
       Some(Array.fill[Model[_]](epm.length)(null))
     } else None
 
@@ -314,6 +314,11 @@ class TrainValidationSplitModel private[ml] (
   override def write: TrainValidationSplitModel.TrainValidationSplitModelWriter = {
     new TrainValidationSplitModel.TrainValidationSplitModelWriter(this)
   }
+
+  @Since("3.0.0")
+  override def toString: String = {
+    s"TrainValidationSplitModel: uid=$uid, bestModel=$bestModel, trainRatio=${$(trainRatio)}"
+  }
 }
 
 @Since("2.0.0")
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
index d2b8751360..07116606df 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
@@ -2767,7 +2767,7 @@ class LogisticRegressionSuite extends MLTest with DefaultReadWriteTest {
 
   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"
+    val expected = "LogisticRegressionModel: uid=logReg, numClasses=2, numFeatures=3"
     assert(model.toString === expected)
   }
 }
diff --git a/python/pyspark/ml/classification.py b/python/pyspark/ml/classification.py
index c5cdf35729..f9465bffc9 100644
--- a/python/pyspark/ml/classification.py
+++ b/python/pyspark/ml/classification.py
@@ -594,7 +594,7 @@ class LogisticRegression(JavaProbabilisticClassifier, _LogisticRegressionParams,
     >>> blorModel.intercept == model2.intercept
     True
     >>> model2
-    LogisticRegressionModel: uid = ..., numClasses = 2, numFeatures = 2
+    LogisticRegressionModel: uid=..., numClasses=2, numFeatures=2
 
     .. versionadded:: 1.3.0
     """
@@ -1146,7 +1146,7 @@ class DecisionTreeClassifier(JavaProbabilisticClassifier, _DecisionTreeClassifie
     >>> model.numClasses
     2
     >>> print(model.toDebugString)
-    DecisionTreeClassificationModel (uid=...) of depth 1 with 3 nodes...
+    DecisionTreeClassificationModel...depth=1, numNodes=3...
     >>> test0 = spark.createDataFrame([(Vectors.dense(-1.0),)], ["features"])
     >>> model.predict(test0.head().features)
     0.0
@@ -1183,7 +1183,7 @@ class DecisionTreeClassifier(JavaProbabilisticClassifier, _DecisionTreeClassifie
     >>> dt3 = DecisionTreeClassifier(maxDepth=2, weightCol="weight", labelCol="indexed")
     >>> model3 = dt3.fit(td3)
     >>> print(model3.toDebugString)
-    DecisionTreeClassificationModel (uid=...) of depth 1 with 3 nodes...
+    DecisionTreeClassificationModel...depth=1, numNodes=3...
 
     .. versionadded:: 1.4.0
     """
@@ -1394,7 +1394,7 @@ class RandomForestClassifier(JavaProbabilisticClassifier, _RandomForestClassifie
     >>> model.transform(test1).head().prediction
     1.0
     >>> model.trees
-    [DecisionTreeClassificationModel (uid=...) of depth..., DecisionTreeClassificationModel...]
+    [DecisionTreeClassificationModel...depth=..., DecisionTreeClassificationModel...]
     >>> rfc_path = temp_path + "/rfc"
     >>> rf.save(rfc_path)
     >>> rf2 = RandomForestClassifier.load(rfc_path)
@@ -1651,7 +1651,7 @@ class GBTClassifier(JavaProbabilisticClassifier, _GBTClassifierParams,
     >>> model.totalNumNodes
     15
     >>> print(model.toDebugString)
-    GBTClassificationModel (uid=...)...with 5 trees...
+    GBTClassificationModel...numTrees=5...
     >>> gbtc_path = temp_path + "gbtc"
     >>> gbt.save(gbtc_path)
     >>> gbt2 = GBTClassifier.load(gbtc_path)
@@ -1665,7 +1665,7 @@ class GBTClassifier(JavaProbabilisticClassifier, _GBTClassifierParams,
     >>> model.treeWeights == model2.treeWeights
     True
     >>> model.trees
-    [DecisionTreeRegressionModel (uid=...) of depth..., DecisionTreeRegressionModel...]
+    [DecisionTreeRegressionModel...depth=..., DecisionTreeRegressionModel...]
     >>> validation = spark.createDataFrame([(0.0, Vectors.dense(-1.0),)],
     ...              ["indexed", "features"])
     >>> model.evaluateEachIteration(validation)
diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py
index e96e13b564..84e39a035d 100644
--- a/python/pyspark/ml/regression.py
+++ b/python/pyspark/ml/regression.py
@@ -800,7 +800,7 @@ class DecisionTreeRegressor(JavaPredictor, _DecisionTreeRegressorParams, JavaMLW
     >>> dt3 = DecisionTreeRegressor(maxDepth=2, weightCol="weight", varianceCol="variance")
     >>> model3 = dt3.fit(df3)
     >>> print(model3.toDebugString)
-    DecisionTreeRegressionModel (uid=...) of depth 1 with 3 nodes...
+    DecisionTreeRegressionModel...depth=1, numNodes=3...
 
     .. versionadded:: 1.4.0
     """
@@ -1018,7 +1018,7 @@ class RandomForestRegressor(JavaPredictor, _RandomForestRegressorParams, JavaMLW
     >>> model.numFeatures
     1
     >>> model.trees
-    [DecisionTreeRegressionModel (uid=...) of depth..., DecisionTreeRegressionModel...]
+    [DecisionTreeRegressionModel...depth=..., DecisionTreeRegressionModel...]
     >>> model.getNumTrees
     2
     >>> test1 = spark.createDataFrame([(Vectors.sparse(1, [0], [1.0]),)], ["features"])
@@ -1265,7 +1265,7 @@ class GBTRegressor(JavaPredictor, _GBTRegressorParams, JavaMLWritable, JavaMLRea
     >>> model.treeWeights == model2.treeWeights
     True
     >>> model.trees
-    [DecisionTreeRegressionModel (uid=...) of depth..., DecisionTreeRegressionModel...]
+    [DecisionTreeRegressionModel...depth=..., DecisionTreeRegressionModel...]
     >>> validation = spark.createDataFrame([(0.0, Vectors.dense(-1.0))],
     ...              ["label", "features"])
     >>> model.evaluateEachIteration(validation, "squared")