Hi Professor Lin,
It will be great if you could please review the TRON code in breeze and
whether it is similar to the original TRON implementation...Breeze is
already integrated in mllib (we are using BFGS and OWLQN is under works for
mllib LogisticRegression) and comparing with TRON should be qu
Debasish Das writes:
> If the SVM is not already migrated to BFGS, that's the first thing you should
> try...Basically following LBFGS Logistic Regression come up with LBFGS based
> linear SVM...
>
> About integrating TRON in mllib, David already has a version of TRON in
> breeze
> but som
yeah, column normalizarion. for some of the datasets, without doing
this, it will not be converged.
Sincerely,
DB Tsai
---
My Blog: https://www.dbtsai.com
LinkedIn: https://www.linkedin.com/in/dbtsai
On Fri, Oct 24, 2014 at 3:46 PM, Debasish D
You mean row/column normalization of data ? how much performance gain you
saw using that ?
On Fri, Oct 24, 2014 at 3:14 PM, DB Tsai wrote:
> oh, we just train the model in the standardized space which will help
> the convergence of LBFGS. Then we convert the weights to original
> space so the w
oh, we just train the model in the standardized space which will help
the convergence of LBFGS. Then we convert the weights to original
space so the whole thing is transparent to users.
Sincerely,
DB Tsai
---
My Blog: https://www.dbtsai.com
Link
@dbtsai for condition number what did you use ? Diagonal preconditioning of
the inverse of B matrix ? But then B matrix keeps on changing...did u
condition it after every few iterations ?
Will it be possible to put that code in Breeze since it will be very useful
to condition other solvers as well
We don't have SVMWithLBFGS, but you can check out how we implement
LogisticRegressionWithLBFGS, and we also deal with some condition
number improving stuff in LogisticRegressionWithLBFGS which improves
the performance dramatically.
Sincerely,
DB Tsai
--
Oh, I've only seen SVMWithSGD, hadn't realized LBFGS was implemented. I'll
try it out when I have time. Thanks!
--
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If the SVM is not already migrated to BFGS, that's the first thing you
should try...Basically following LBFGS Logistic Regression come up with
LBFGS based linear SVM...
About integrating TRON in mllib, David already has a version of TRON in
breeze but someone needs to validate it for linear SVM an
Just wondering, any update on this? Is there a plan to integrate CJ's work
with mllib? I'm asking since SVM impl in MLLib did not give us good results
and we have to resort to training our svm classifier in a serial manner on
the driver node with liblinear.
Also, it looks like CJ Lin is coming to
I've done some comparisons with my own implementation of TRON on Spark.
From a distributed computing perspective, it does 2x more local work per
iteration than LBFGS, so the parallel isoefficiency is improved slightly.
I think the truncated Newton solver holds some potential because there
have be
Hi Deb,
My co-worker fixed a owlqn bug in breeze, and it's important to have this
to converge to the correct result.
https://github.com/scalanlp/breeze/pull/247
You may want to use the snapshot of breeze to have this fix in.
Sincerely,
DB Tsai
-
Hi Professor Lin,
On our internal datasets, I am getting accuracy at par with glmnet-R for
sparse feature selection from liblinear. The default mllib based gradient
descent was way off. I did not tune learning rate but I run with varying
lambda. Ths feature selection was weak.
I used liblinear c
It seems that the code isn't managed in github. Can be downloaded from
http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/distributed-liblinear/spark/spark-liblinear-1.94.zip
It will be easier to track the changes in github.
Sincerely,
DB Tsai
---
Hi Chieh-Yen,
Great to see the Spark implementation of LIBLINEAR! We will definitely
consider adding a wrapper in MLlib to support it. Is the source code
on github?
Deb, Spark LIBLINEAR uses BSD license, which is compatible with Apache.
Best,
Xiangrui
On Sun, May 11, 2014 at 10:29 AM, Debasish
Hello Prof. Lin,
Awesome news ! I am curious if you have any benchmarks comparing C++ MPI
with Scala Spark liblinear implementations...
Is Spark Liblinear apache licensed or there are any specific restrictions
on using it ?
Except using native blas libraries (which each user has to manage by
pul
Dear Prof. Lin,
Interesting! We had an implementation of L-BFGS in Spark and already merged
in the upstream now.
We read your paper comparing TRON and OWL-QN for logistic regression with
L1 (http://www.csie.ntu.edu.tw/~cjlin/papers/l1.pdf), but it seems that
it's not in the distributed setup.
Wi
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