[SPARK-12346] [ML] Missing attribute names in GLM for vector-type features #10323
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| test("vector attribute generation") { | ||
| val formula = new RFormula().setFormula("id ~ vec") | ||
| val original = sqlContext.createDataFrame( | ||
| Seq((1, Vectors.dense(0.0, 1.0)), (2, Vectors.dense(1.0, 2.0))) |
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Should we support term in R formula is type vector? I think it's illegal in R.
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I think it makes sense when using RFormula in a ML pipeline (not necessarily in R).
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Test build #47806 has finished for PR 10323 at commit
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@ericl this looks great, thanks! |
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…ures Currently `summary()` fails on a GLM model fitted over a vector feature missing ML attrs, since the output feature attrs will also have no name. We can avoid this situation by forcing `VectorAssembler` to make up suitable names when inputs are missing names. cc mengxr Author: Eric Liang <ekl@databricks.com> Closes #10323 from ericl/spark-12346. (cherry picked from commit 5e492e9) Signed-off-by: Xiangrui Meng <meng@databricks.com>
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Merged into master and branch-1.6. Thanks! I created https://issues.apache.org/jira/browse/SPARK-12886 to track some follow-up tasks. |
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Currently
summary()fails on a GLM model fitted over a vector feature missing ML attrs, since the output feature attrs will also have no name. We can avoid this situation by forcingVectorAssemblerto make up suitable names when inputs are missing names.cc @mengxr