Hi Mikhail,
I have followed the MLP user-guide and used the dataset and network
configuration you mentioned. MLP was trained without any issues with default
parameters, that is block size of 128 and 100 iterations.
Source code:
scala> import org.apache.spark.ml.classification.MultilayerPerceptronClassifier
scala> val sqlContext = new org.apache.spark.sql.SQLContext(sc)
scala> val data = sqlContext.read.format("libsvm").load("/data/aloi.scale")
scala> val trainer = new MultilayerPerceptronClassifier().setLayers(Array(128,
128, 1000))
scala> val model = trainer.fit(data)
(after a while)
model: org.apache.spark.ml.classification.MultilayerPerceptronClassificationMode
l = mlpc_fb3bd70d2ef2
It seems that submitting an Issue is premature. Could you share your code
instead?
Best regards, Alexander
Just in case, here is the link to the user guide:
https://spark.apache.org/docs/latest/ml-classification-regression.html#multilayer-perceptron-classifier
From: Yanbo Liang [mailto:yblia...@gmail.com]
Sent: Monday, July 04, 2016 9:58 PM
To: mshiryae <mikhail.shiry...@intel.com>
Cc: user@spark.apache.org
Subject: Re: Spark MLlib: MultilayerPerceptronClassifier error?
Would you mind to file a JIRA to track this issue? I will take a look when I
have time.
2016-07-04 14:09 GMT-07:00 mshiryae
<mikhail.shiry...@intel.com<mailto:mikhail.shiry...@intel.com>>:
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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