[SPARK-14478][ML][MLLIB][DOC] Doc that StandardScaler uses the corrected sample std

mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala

@@ -66,6 +66,11 @@ private[feature] trait StandardScalerParams extends Params with HasInputCol with
  * :: Experimental ::
  * Standardizes features by removing the mean and scaling to unit variance using column summary
  * statistics on the samples in the training set.
+ *
+ * The "unit std" is computed using the
+ * [[https://en.wikipedia.org/wiki/Standard_deviation#Corrected_sample_standard_deviation
+ *   corrected sample standard deviation]],
+ * which is computed as the square root of the unbiased sample variance.
  */
 @Experimental
 class StandardScaler(override val uid: String) extends Estimator[StandardScalerModel]

mllib/src/main/scala/org/apache/spark/mllib/feature/StandardScaler.scala

@@ -27,6 +27,11 @@ import org.apache.spark.rdd.RDD
  * Standardizes features by removing the mean and scaling to unit std using column summary
  * statistics on the samples in the training set.
  *
+ * The "unit std" is computed using the
+ * [[https://en.wikipedia.org/wiki/Standard_deviation#Corrected_sample_standard_deviation
+ *   corrected sample standard deviation]],
+ * which is computed as the square root of the unbiased sample variance.
+ *
  * @param withMean False by default. Centers the data with mean before scaling. It will build a
  *                 dense output, so this does not work on sparse input and will raise an exception.
  * @param withStd True by default. Scales the data to unit standard deviation.