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https://issues.apache.org/jira/browse/SPARK-16377?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Nicholas Chammas updated SPARK-16377:
-------------------------------------
    Component/s:     (was: MLilb)
                 MLlib

> Spark MLlib: MultilayerPerceptronClassifier - error while training
> ------------------------------------------------------------------
>
>                 Key: SPARK-16377
>                 URL: https://issues.apache.org/jira/browse/SPARK-16377
>             Project: Spark
>          Issue Type: Bug
>          Components: ML, MLlib
>    Affects Versions: 1.5.2
>            Reporter: Mikhail Shiryaev
>
> Hi, 
> I am trying to train model by MultilayerPerceptronClassifier. 
> It works on sample data from 
> data/mllib/sample_multiclass_classification_data.txt with 4 features, 3 
> classes and layers [4, 4, 3]. 
> But when I try to use other input files with other features and classes (from 
> here for example: 
> https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass.html) 
> then I get errors. 
> Example: 
> Input file aloi (128 features, 1000 classes, layers [128, 128, 1000]): 
> with block size = 1: 
> ERROR StrongWolfeLineSearch: Encountered bad values in function evaluation. 
> Decreasing step size to Infinity 
> ERROR LBFGS: Failure! Resetting history: breeze.optimize.FirstOrderException: 
> Line search failed 
> ERROR LBFGS: Failure again! Giving up and returning. Maybe the objective is 
> just poorly behaved? 
> with default block size = 128: 
>  java.lang.ArrayIndexOutOfBoundsException 
>   at java.lang.System.arraycopy(Native Method) 
>   at 
> org.apache.spark.ml.ann.DataStacker$$anonfun$3$$anonfun$apply$3$$anonfun$apply$4.apply(Layer.scala:629)
>  
>   at 
> org.apache.spark.ml.ann.DataStacker$$anonfun$3$$anonfun$apply$3$$anonfun$apply$4.apply(Layer.scala:628)
>  
>    at scala.collection.immutable.List.foreach(List.scala:381) 
>    at 
> org.apache.spark.ml.ann.DataStacker$$anonfun$3$$anonfun$apply$3.apply(Layer.scala:628)
>  
>    at 
> org.apache.spark.ml.ann.DataStacker$$anonfun$3$$anonfun$apply$3.apply(Layer.scala:624)
>  
> Even if I modify sample_multiclass_classification_data.txt file (rename all 
> 4-th features to 5-th) and run with layers [5, 5, 3] then I also get the same 
> errors as for file above. 
> So to resume: 
> I can't run training with default block size and with more than 4 features. 
> If I set  block size to 1 then some actions are happened but I get errors 
> from LBFGS. 
> It is reproducible with Spark 1.5.2 and from master branch on github (from 
> 4-th July). 
> Did somebody already met with such behavior? 
> Is there bug in MultilayerPerceptronClassifier or I use it incorrectly? 
> Thanks.



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