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e.g., in `BisectingKMeans`, this patch changes
val data = dataset.select(col($(featuresCol))).rdd.map { case
Row(point: Vector) => point }
to
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@viirya can you provide an example of how this works for use here in this
PR?
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encoder now supports UDTs. You just need to declare one before you want to
use it.
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@viirya yeah, sorry I meant we should create an encoder that can be used in
`ml`... whether an implicit or explicit.
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/Predictor.scala ---
@@ -121,9 +121,9 @@ abstract class Predictor[
* and put it in an RDD with
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We have no implicit encoder for vector udt. But we can explicitly create it.
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/Predictor.scala ---
@@ -121,9 +121,9 @@ abstract class Predictor[
* and put it in an RDD with strong
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We should definitely have an encoder for vector udts... cc @dbtsai @viirya
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Vector, LabeledPoint, Instance and AFTPoint can not be used in `DataSet.as`
now
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Now, Encoder for Vector is missing...
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