[SPARK-15617][ML][DOC] Clarify that fMeasure in MulticlassMetrics is "micro" f1_score

## What changes were proposed in this pull request?
1, del precision,recall in  `ml.MulticlassClassificationEvaluator`
2, update user guide for `mlllib.weightedFMeasure`

## How was this patch tested?
local build

Author: Ruifeng Zheng <ruifengz@foxmail.com>

Closes #13390 from zhengruifeng/clarify_f1.

2 files changed, 6 insertions, 8 deletions

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 0b84e0a3fa..794b1e7d9d 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
@@ -39,16 +39,16 @@ class MulticlassClassificationEvaluator @Since("1.5.0") (@Since("1.5.0") overrid
   def this() = this(Identifiable.randomUID("mcEval"))
 
   /**
-   * param for metric name in evaluation (supports `"f1"` (default), `"precision"`, `"recall"`,
-   * `"weightedPrecision"`, `"weightedRecall"`, `"accuracy"`)
+   * param for metric name in evaluation (supports `"f1"` (default), `"weightedPrecision"`,
+   * `"weightedRecall"`, `"accuracy"`)
    * @group param
    */
   @Since("1.5.0")
   val metricName: Param[String] = {
-    val allowedParams = ParamValidators.inArray(Array("f1", "precision",
-      "recall", "weightedPrecision", "weightedRecall", "accuracy"))
+    val allowedParams = ParamValidators.inArray(Array("f1", "weightedPrecision",
+      "weightedRecall", "accuracy"))
     new Param(this, "metricName", "metric name in evaluation " +
-      "(f1|precision|recall|weightedPrecision|weightedRecall|accuracy)", allowedParams)
+      "(f1|weightedPrecision|weightedRecall|accuracy)", allowedParams)
   }
 
   /** @group getParam */
@@ -82,8 +82,6 @@ class MulticlassClassificationEvaluator @Since("1.5.0") (@Since("1.5.0") overrid
     val metrics = new MulticlassMetrics(predictionAndLabels)
     val metric = $(metricName) match {
       case "f1" => metrics.weightedFMeasure
-      case "precision" => metrics.accuracy
-      case "recall" => metrics.accuracy
       case "weightedPrecision" => metrics.weightedPrecision
       case "weightedRecall" => metrics.weightedRecall
       case "accuracy" => metrics.accuracy
diff --git a/mllib/src/test/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluatorSuite.scala
index 522f6675d7..1a3a8a13a2 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluatorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluatorSuite.scala
@@ -33,7 +33,7 @@ class MulticlassClassificationEvaluatorSuite
     val evaluator = new MulticlassClassificationEvaluator()
       .setPredictionCol("myPrediction")
       .setLabelCol("myLabel")
-      .setMetricName("recall")
+      .setMetricName("accuracy")
     testDefaultReadWrite(evaluator)
   }