Mikhail Shiryaev created SPARK-16377:
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Summary: 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, MLilb
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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