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From "Mikhail Shiryaev (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (SPARK-16377) Spark MLlib: MultilayerPerceptronClassifier - error while training
Date Mon, 21 Nov 2016 10:55:58 GMT

    [ https://issues.apache.org/jira/browse/SPARK-16377?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15683194#comment-15683194
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Mikhail Shiryaev edited comment on SPARK-16377 at 11/21/16 10:55 AM:
---------------------------------------------------------------------

Yes, you can close it.
The original problem has been resolved.
Thank you.


was (Author: mshiryae):
Yes, you can close it.
The original problem has been resolved.
Thanks you.

> 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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