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Posted to issues@spark.apache.org by "Yanbo Liang (JIRA)" <ji...@apache.org> on 2016/05/05 12:42:12 UTC
[jira] [Updated] (SPARK-15153) SparkR spark.naiveBayes throws error
when label is numeric type
[ https://issues.apache.org/jira/browse/SPARK-15153?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Yanbo Liang updated SPARK-15153:
--------------------------------
Summary: SparkR spark.naiveBayes throws error when label is numeric type (was: SparkR spark.naiveBayes error when label is numeric type)
> SparkR spark.naiveBayes throws error when label is numeric type
> ---------------------------------------------------------------
>
> Key: SPARK-15153
> URL: https://issues.apache.org/jira/browse/SPARK-15153
> Project: Spark
> Issue Type: Bug
> Components: ML, SparkR
> Reporter: Yanbo Liang
>
> When the type of label of dataset is numeric, SparkR spark.naiveBayes will throw error when training. This bug is easy to reproduce:
> {code}
> t <- as.data.frame(Titanic)
> t1 <- t[t$Freq > 0, -5]
> t1$NumericSurvived <- ifelse(t1$Survived == "No", 0, 1)
> t2 <- t1[-4]
> df <- suppressWarnings(createDataFrame(sqlContext, t2))
> m <- spark.naiveBayes(df, NumericSurvived ~ .)
> 16/05/05 03:26:17 ERROR RBackendHandler: fit on org.apache.spark.ml.r.NaiveBayesWrapper failed
> Error in invokeJava(isStatic = TRUE, className, methodName, ...) :
> java.lang.ClassCastException: org.apache.spark.ml.attribute.UnresolvedAttribute$ cannot be cast to org.apache.spark.ml.attribute.NominalAttribute
> at org.apache.spark.ml.r.NaiveBayesWrapper$.fit(NaiveBayesWrapper.scala:66)
> at org.apache.spark.ml.r.NaiveBayesWrapper.fit(NaiveBayesWrapper.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:141)
> at org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:86)
> at org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:38)
> at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
> at io.netty.channel.AbstractChannelHandlerContext.invo
> {code}
> In RFormula, the response variable type can be numeric or string. If it's string, RFormula will transform it to DoubleType by StringIndexer; otherwise, RFormula will directly use it at model training (and assume it was numbered from 0, ..., maxLabelIndex). When we extract labels at SparkR naiveBayes wrapper, we should handle it according the type of the response variable (string or numeric).
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