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Posted to issues@spark.apache.org by "Yanbo Liang (JIRA)" <ji...@apache.org> on 2016/11/11 10:26:58 UTC
[jira] [Updated] (SPARK-18412) SparkR spark.randomForest
classification throws exception when training on libsvm data
[ https://issues.apache.org/jira/browse/SPARK-18412?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Yanbo Liang updated SPARK-18412:
--------------------------------
Description:
{{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}
16/11/11 02:16:40 ERROR RBackendHandler: fit on org.apache.spark.ml.r.RandomForestClassifierWrapper failed
java.lang.reflect.InvocationTargetException
......
Caused by: java.lang.IllegalArgumentException: requirement failed: If label column already exists, forceIndexLabel can not be set with true.
......
{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).
was:
{{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}
16/11/11 02:16:40 ERROR RBackendHandler: fit on org.apache.spark.ml.r.RandomForestClassifierWrapper failed
java.lang.reflect.InvocationTargetException
......
Caused by: java.lang.IllegalArgumentException: requirement failed: If label column already exists, forceIndexLabel can not be set with true.
......
{code}
> 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}
> 16/11/11 02:16:40 ERROR RBackendHandler: fit on org.apache.spark.ml.r.RandomForestClassifierWrapper failed
> java.lang.reflect.InvocationTargetException
> ......
> Caused by: java.lang.IllegalArgumentException: requirement failed: If label column already exists, forceIndexLabel can not be set with true.
> ......
> {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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