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Posted to issues@spark.apache.org by "Xusen Yin (JIRA)" <ji...@apache.org> on 2016/03/16 06:00:36 UTC
[jira] [Comment Edited] (SPARK-13641) getModelFeatures of
ml.api.r.SparkRWrapper cannot (always) reveal the original column names
[ https://issues.apache.org/jira/browse/SPARK-13641?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15196765#comment-15196765 ]
Xusen Yin edited comment on SPARK-13641 at 3/16/16 5:00 AM:
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I gonna close this JIRA since I find that it is intended to do so by One-hot encoder to index discrete feature.
was (Author: yinxusen):
[~muralidh] I gonna close this JIRA since I find that it is intended to do so by One-hot encoder to index discrete feature.
> getModelFeatures of ml.api.r.SparkRWrapper cannot (always) reveal the original column names
> -------------------------------------------------------------------------------------------
>
> Key: SPARK-13641
> URL: https://issues.apache.org/jira/browse/SPARK-13641
> Project: Spark
> Issue Type: Bug
> Components: ML, SparkR
> Reporter: Xusen Yin
> Priority: Minor
>
> getModelFeatures of ml.api.r.SparkRWrapper cannot (always) reveal the original column names. Let's take the HouseVotes84 data set as an example:
> {code}
> case m: XXXModel =>
> val attrs = AttributeGroup.fromStructField(
> m.summary.predictions.schema(m.summary.featuresCol))
> attrs.attributes.get.map(_.name.get)
> {code}
> The code above gets features' names from the features column. Usually, the features column is generated by RFormula. The latter has a VectorAssembler in it, which leads the output attributes not equal with the original ones.
> E.g., we want to learn the HouseVotes84's features' name "V1, V2, ..., V16". But with RFormula, we can only get "V1_n, V2_y, ..., V16_y" because [the transform function of VectorAssembler|https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala#L75] adds salts of the column names.
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