[SPARK-13761][ML] Deprecate validateParams

## What changes were proposed in this pull request?

Deprecate validateParams() method here: https://github.com/apache/spark/blob/035d3acdf3c1be5b309a861d5c5beb803b946b5e/mllib/src/main/scala/org/apache/spark/ml/param/params.scala#L553
Move all functionality in overridden methods to transformSchema().
Check docs to make sure they indicate complex Param interaction checks should be done in transformSchema.

## How was this patch tested?

unit tests

Author: Yuhao Yang <hhbyyh@gmail.com>

Closes #11620 from hhbyyh/depreValid.

3 files changed, 17 insertions, 13 deletions

diff --git a/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala b/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala
index a3a8f65eac..dd3f4c6e53 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala
@@ -138,16 +138,18 @@ class LDASuite extends SparkFunSuite with MLlibTestSparkContext with DefaultRead
       new LDA().setTopicConcentration(-1.1)
     }
 
-    // validateParams()
-    lda.validateParams()
+    val dummyDF = sqlContext.createDataFrame(Seq(
+      (1, Vectors.dense(1.0, 2.0)))).toDF("id", "features")
+    // validate parameters
+    lda.transformSchema(dummyDF.schema)
     lda.setDocConcentration(1.1)
-    lda.validateParams()
+    lda.transformSchema(dummyDF.schema)
     lda.setDocConcentration(Range(0, lda.getK).map(_ + 2.0).toArray)
-    lda.validateParams()
+    lda.transformSchema(dummyDF.schema)
     lda.setDocConcentration(Range(0, lda.getK - 1).map(_ + 2.0).toArray)
     withClue("LDA docConcentration validity check failed for bad array length") {
       intercept[IllegalArgumentException] {
-        lda.validateParams()
+        lda.transformSchema(dummyDF.schema)
       }
     }
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala
index 035bfc07b6..87206c777e 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala
@@ -57,13 +57,15 @@ class MinMaxScalerSuite extends SparkFunSuite with MLlibTestSparkContext with De
 
   test("MinMaxScaler arguments max must be larger than min") {
     withClue("arguments max must be larger than min") {
+      val dummyDF = sqlContext.createDataFrame(Seq(
+        (1, Vectors.dense(1.0, 2.0)))).toDF("id", "feature")
       intercept[IllegalArgumentException] {
-        val scaler = new MinMaxScaler().setMin(10).setMax(0)
-        scaler.validateParams()
+        val scaler = new MinMaxScaler().setMin(10).setMax(0).setInputCol("feature")
+        scaler.transformSchema(dummyDF.schema)
       }
       intercept[IllegalArgumentException] {
-        val scaler = new MinMaxScaler().setMin(0).setMax(0)
-        scaler.validateParams()
+        val scaler = new MinMaxScaler().setMin(0).setMax(0).setInputCol("feature")
+        scaler.transformSchema(dummyDF.schema)
       }
     }
   }
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala
index 94191e5df3..6bb4678dc5 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala
@@ -21,21 +21,21 @@ import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.attribute.{Attribute, AttributeGroup, NumericAttribute}
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.DefaultReadWriteTest
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
+import org.apache.spark.mllib.linalg.{Vector, Vectors, VectorUDT}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.{DataFrame, Row}
-import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.types.{StructField, StructType}
 
 class VectorSlicerSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
 
   test("params") {
-    val slicer = new VectorSlicer
+    val slicer = new VectorSlicer().setInputCol("feature")
     ParamsSuite.checkParams(slicer)
     assert(slicer.getIndices.length === 0)
     assert(slicer.getNames.length === 0)
     withClue("VectorSlicer should not have any features selected by default") {
       intercept[IllegalArgumentException] {
-        slicer.validateParams()
+        slicer.transformSchema(StructType(Seq(StructField("feature", new VectorUDT, true))))
       }
     }
   }