[
https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12802032#action_12802032
]
Olivier Grisel commented on MAHOUT-228:
---------------------------------------
For the records: I am working adding more tests and debugging in the following
branch (keps in sync with the trunk) hosted on github:
http://github.com/ogrisel/mahout/commits/MAHOUT-228
Fixed so far:
- convergence issues (inconstency on the index of the 'missing' beta row)
- make sure that L1 is sparsity inducing my apply eager post update
regularization
Still TODO (independently of Ted's TODOs) - migh be splitted into specific jira
issues:
- test that highly redundant dataset can lean to very sparse models with L1
prior
- an hadoop driver to do // extraction vector features of documents using the
Randomizer classes
- an hadoop driver to do // cross validation and confusion matrix evaluation
(along with confidence interval)
- an hadoop driver to perform hyperparameters grid search (lambda, priorfunc,
learning rate, ...)
- a sample hadoop driver to categorize wikipedia articles by country
- profile it a bit
> Need sequential logistic regression implementation using SGD techniques
> -----------------------------------------------------------------------
>
> Key: MAHOUT-228
> URL: https://issues.apache.org/jira/browse/MAHOUT-228
> Project: Mahout
> Issue Type: New Feature
> Components: Classification
> Reporter: Ted Dunning
> Fix For: 0.3
>
> Attachments: logP.csv, MAHOUT-228-3.patch, r.csv, sgd-derivation.pdf,
> sgd-derivation.tex, sgd.csv
>
>
> Stochastic gradient descent (SGD) is often fast enough for highly scalable
> learning (see Vowpal Wabbit, http://hunch.net/~vw/).
> I often need to have a logistic regression in Java as well, so that is a
> reasonable place to start.
--
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.
