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https://issues.apache.org/jira/browse/SPARK-18412?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15656892#comment-15656892
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Apache Spark commented on SPARK-18412:
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User 'yanboliang' has created a pull request for this issue:
https://github.com/apache/spark/pull/15851
> SparkR spark.randomForest classification throws exception when training on
> libsvm data
> --------------------------------------------------------------------------------------
>
> Key: SPARK-18412
> URL: https://issues.apache.org/jira/browse/SPARK-18412
> Project: Spark
> Issue Type: Bug
> Components: ML, SparkR
> Reporter: Yanbo Liang
>
> {{spark.randomForest}} classification throws exception when training on
> libsvm data. It can be reproduced as following:
> {code}
> df <- read.df("data/mllib/sample_multiclass_classification_data.txt", source
> = "libsvm")
> model <- spark.randomForest(df, label ~ features, "classification")
> {code}
> The exception is:
> {code}
> Error in handleErrors(returnStatus, conn) :
> java.lang.IllegalArgumentException: requirement failed: If label column
> already exists, forceIndexLabel can not be set with true.
> at scala.Predef$.require(Predef.scala:224)
> at
> org.apache.spark.ml.feature.RFormula.transformSchema(RFormula.scala:205)
> at org.apache.spark.ml.PipelineStage.transformSchema(Pipeline.scala:70)
> at org.apache.spark.ml.feature.RFormula.fit(RFormula.scala:136)
> at
> org.apache.spark.ml.r.RandomForestClassifierWrapper$.fit(RandomForestClassificationWrapper.scala:86)
> at
> org.apache.spark.ml.r.RandomForestClassifierWrapper.fit(RandomForestClassificationWrapper.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> org.apache.spark.api.r.RBackendHandler.handleMethodCall(RBackendHandler.scala:172)
> {code}
> This error is caused by the label column of the R formula already exists, we
> can not force to index label. However, it must index the label for
> classification algorithms, so we need to rename the RFormula.labelCol to a
> new value and then we can index the original label.
> This issue also appears at other algorithms: spark.naiveBayes, spark.glm(only
> for binomial family) and spark.gbt (only for classification).
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