RE: Spark MLlib: MultilayerPerceptronClassifier error?
Hi Alexander,
I used the same example from MLP user guide but on Java language.
I modified an example a little bit and there was my nasty bug that I haven’t
noticed (some inconsistence between layers and real feature count).
After fixing that MLP works on my test.
So here is my inadvertence, sorry.
Best regards,
Mikhail Shiryaev
From: Ulanov, Alexander [mailto:alexander.ula...@hpe.com]
Sent: Tuesday, July 5, 2016 9:32 PM
To: Yanbo Liang <yblia...@gmail.com>; Shiryaev, Mikhail
<mikhail.shiry...@intel.com>
Cc: user@spark.apache.org
Subject: RE: Spark MLlib: MultilayerPerceptronClassifier error?
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<mailto:mikhail.shiry...@intel.com>>
Cc: user@spark.apache.org<mailto: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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RE: Spark MLlib: MultilayerPerceptronClassifier error?
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.
--
View this message in context:
http://apache-spark-user-list.1001560.n3.nabble.com/Spark-MLlib-MultilayerPerceptronClassifier-error-tp27279.html
Sent from the Apache Spark User List mailing list archive at Nabble.com.
-
To unsubscribe e-mail:
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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>: > 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. > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Spark-MLlib-MultilayerPerceptronClassifier-error-tp27279.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > - > To unsubscribe e-mail: user-unsubscr...@spark.apache.org > >
Spark MLlib: MultilayerPerceptronClassifier error?
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. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Spark-MLlib-MultilayerPerceptronClassifier-error-tp27279.html Sent from the Apache Spark User List mailing list archive at Nabble.com. - To unsubscribe e-mail: user-unsubscr...@spark.apache.org
