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test this please
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
---
@@ -114,25 +177,29 @@ class RFormula(override val uid: String)
}
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
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@@ -62,19 +77,72 @@ class RFormula(override val uid: String)
/** @group
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
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--- Diff:
mllib/src/test/scala/org/apache/spark/ml/feature/RFormulaSuite.scala ---
@@ -48,55 +49,59 @@ class RFormulaSuite extends SparkFunSuite with
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
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@@ -114,25 +177,29 @@ class RFormula(override val uid: String)
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--- Diff:
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
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@@ -62,19 +77,72 @@ class RFormula(override val uid: String)
/** @group
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test this please
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--- Diff:
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/** @group
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LGTM pending Jenkins.
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Merged into master. Thanks!
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ptal
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
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@@ -130,9 +173,52 @@ class RFormula(override val uid: String)
Label
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
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Label
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
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/** @group
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Github user ericl commented on the pull request:
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Hmm, I guess that is pretty harmless though. Will do.
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Github user mengxr commented on the pull request:
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You can construct a `Pipeline` object in `RFormula.fit`, which contains all
`StringIndexer`, `OneHotEncoder`, etc. Then call `Pipeline.fit` in
`RFormula.fit` and get the
Github user ericl commented on the pull request:
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@mengxr to clarify, not calling `StringIndexer.fit` in `RFormula.fit` means
RFormulaModel will have a reference to the original fitted dataset, correct?
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
---
@@ -62,19 +77,60 @@ class RFormula(override val uid: String)
/** @group
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
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@@ -130,9 +173,52 @@ class RFormula(override val uid: String)
Label
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@ericl I think it is simpler to construct a `pipeline` in `RFormula.fit`
without calling `StringIndexer.fit` explicitly. That leaves space for
`pipeline.fit`
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
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@@ -130,9 +173,52 @@ class RFormula(override val uid: String)
Label
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GitHub user ericl opened a pull request:
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[SPARK-9230] [ML] Support StringType features in RFormula
This adds StringType feature support via OneHotEncoder. As part of this
task it was necessary to change RFormula to an Estimator, so that
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