Github user yanboliang commented on a diff in the pull request:

    https://github.com/apache/spark/pull/18538#discussion_r137239906
  
    --- Diff: 
mllib/src/main/scala/org/apache/spark/ml/evaluation/ClusteringEvaluator.scala 
---
    @@ -0,0 +1,396 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.spark.ml.evaluation
    +
    +import org.apache.spark.SparkContext
    +import org.apache.spark.annotation.{Experimental, Since}
    +import org.apache.spark.broadcast.Broadcast
    +import org.apache.spark.ml.linalg.{BLAS, DenseVector, Vector, Vectors, 
VectorUDT}
    +import org.apache.spark.ml.param.ParamMap
    +import org.apache.spark.ml.param.shared.{HasFeaturesCol, HasPredictionCol}
    +import org.apache.spark.ml.util.{DefaultParamsReadable, 
DefaultParamsWritable, Identifiable, SchemaUtils}
    +import org.apache.spark.sql.{DataFrame, Dataset}
    +import org.apache.spark.sql.functions.{avg, col, udf}
    +import org.apache.spark.sql.types.IntegerType
    +
    +/**
    + * :: Experimental ::
    + * Evaluator for clustering results.
    + * The metric computes the Silhouette measure
    + * using the squared Euclidean distance.
    + *
    + * The Silhouette is a measure for the validation
    + * of the consistency within clusters. It ranges
    + * between 1 and -1, where a value close to 1
    + * means that the points in a cluster are close
    + * to the other points in the same cluster and
    + * far from the points of the other clusters.
    + */
    +@Experimental
    +@Since("2.3.0")
    +class ClusteringEvaluator (val uid: String)
    +  extends Evaluator with HasPredictionCol with HasFeaturesCol with 
DefaultParamsWritable {
    +
    +  def this() = this(Identifiable.randomUID("cluEval"))
    +
    +  override def copy(pMap: ParamMap): ClusteringEvaluator = 
this.defaultCopy(pMap)
    +
    +  override def isLargerBetter: Boolean = true
    +
    +  /** @group setParam */
    +  @Since("2.3.0")
    +  def setPredictionCol(value: String): this.type = set(predictionCol, 
value)
    +
    +  /** @group setParam */
    +  @Since("2.3.0")
    +  def setFeaturesCol(value: String): this.type = set(featuresCol, value)
    +
    +  @Since("2.3.0")
    +  override def evaluate(dataset: Dataset[_]): Double = {
    +    SchemaUtils.checkColumnType(dataset.schema, $(featuresCol), new 
VectorUDT)
    +    SchemaUtils.checkColumnType(dataset.schema, $(predictionCol), 
IntegerType)
    +
    +    SquaredEuclideanSilhouette.computeSilhouetteScore(
    +      dataset,
    +      $(predictionCol),
    +      $(featuresCol)
    +    )
    +  }
    +}
    +
    +
    +object ClusteringEvaluator
    --- End diff --
    
    ```@Since("2.3.0")``` 


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