Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/17864#discussion_r118600408
--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/Imputer.scala ---
@@ -94,12 +94,13 @@ private[feature] trait ImputerParams extends Params
with HasInputCols {
* :: Experimental ::
* Imputation estimator for completing missing values, either using the
mean or the median
* of the columns in which the missing values are located. The input
columns should be of
- * DoubleType or FloatType. Currently Imputer does not support categorical
features
+ * numeric type. Currently Imputer does not support categorical features
* (SPARK-15041) and possibly creates incorrect values for a categorical
feature.
*
* Note that the mean/median value is computed after filtering out missing
values.
* All Null values in the input columns are treated as missing, and so are
also imputed. For
* computing median, DataFrameStatFunctions.approxQuantile is used with a
relative error of 0.001.
+ * The output column is always of Double type regardless of the input
column type.
--- End diff --
@MLnick Here is the note on always returning Double type.
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