[SPARK-21210][DOC][ML] Javadoc 8 fixes for ML shared param traits

PR #15999 included fixes for doc strings in the ML shared param traits (occurrences of `>` and `>=`).

This PR simply uses the HTML-escaped version of the param doc to embed into the Scaladoc, to ensure that when `SharedParamsCodeGen` is run, the generated javadoc will be compliant for Java 8.

## How was this patch tested?
Existing tests

Author: Nick Pentreath <nickp@za.ibm.com>

Closes #18420 from MLnick/shared-params-javadoc8.

mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala

@@ -20,6 +20,7 @@ package org.apache.spark.ml.param.shared
 import java.io.PrintWriter
 
 import scala.reflect.ClassTag
+import scala.xml.Utility
 
 /**
  * Code generator for shared params (sharedParams.scala). Run under the Spark folder with
@@ -167,6 +168,8 @@ private[shared] object SharedParamsCodeGen {
       "def"
     }
 
+    val htmlCompliantDoc = Utility.escape(doc)
+
     s"""
       |/**
       | * Trait for shared param $name$defaultValueDoc.
@@ -174,7 +177,7 @@ private[shared] object SharedParamsCodeGen {
       |private[ml] trait Has$Name extends Params {
       |
       |  /**
-      |   * Param for $doc.
+      |   * Param for $htmlCompliantDoc.
       |   * @group ${groupStr(0)}
       |   */
       |  final val $name: $Param = new $Param(this, "$name", "$doc"$isValid)

mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala

@@ -176,7 +176,7 @@ private[ml] trait HasThreshold extends Params {
 private[ml] trait HasThresholds extends Params {
 
   /**
-   * Param for Thresholds in multi-class classification to adjust the probability of predicting each class. Array must have length equal to the number of classes, with values > 0 excepting that at most one value may be 0. The class with largest value p/t is predicted, where p is the original probability of that class and t is the class's threshold.
+   * Param for Thresholds in multi-class classification to adjust the probability of predicting each class. Array must have length equal to the number of classes, with values > 0 excepting that at most one value may be 0. The class with largest value p/t is predicted, where p is the original probability of that class and t is the class's threshold.
    * @group param
    */
   final val thresholds: DoubleArrayParam = new DoubleArrayParam(this, "thresholds", "Thresholds in multi-class classification to adjust the probability of predicting each class. Array must have length equal to the number of classes, with values > 0 excepting that at most one value may be 0. The class with largest value p/t is predicted, where p is the original probability of that class and t is the class's threshold", (t: Array[Double]) => t.forall(_ >= 0) && t.count(_ == 0) <= 1)