[pymvpa] Announcement: 0.4.4 release (git/sources/Debian/Ubuntu/Windows/Fedora/SuSe/RedHat/CentOS)

[Matthias Ekman]

Hi,

thanks for the release!

>     - Do not derive NaN scaling for SVM's C whenever data is
>       degenerate (lead to never finishing SVM training).

Is this only relevant for automatic scaling of value according to the
norm of the data (C=-1)?

is this problem 'always' leading to never finished SVM training, or do
you suggest to re-run previous (finished) analysis?

Thanks,
 Matthias

PyMVPA Team wrote:
> Dear PyMVPA users,
> 
> I am glad to announce that we are releasing 0.4.4 version of
> PyMVPA.
> 
> So far we have:
>   * pushed/tagged sources in git repository
>     (git://git.debian.org/git/pkg-exppsy/pymvpa.git)
>   * uploaded Debian packages into Debian/sid proper
>     (should become available later on today)
>   * uploaded Debian packages into http://neuro.debian.org
>     repository for:
> 	+ Debian: lenny, squeeze
> 	+ Ubuntu: jaunty, karmic
> 	(http://neuro.debian.net/pkgs/python-mvpa.html)
>   * source tarballs and windows installer available from
>     usual location
>     https://alioth.debian.org/frs/?group_id=30954
>   * RPM-based GNU/Linux Distributions
> 	available from OpenSUSE Build Service. See
>     http://pymvpa.org/installation.html#rpm-based-gnu-linux-distributions 
> 
> This is primarily a bugfix release, probably the last in 0.4 series since
> development for 0.5 release is leaping forward -- please keep an eye on the
> mailing list for the announcement of availability of snapshots of development
> version.
> 
> 
> Changelog for the release is:
> 
>   * New functionality (19 NF commits):
> 
>     - :class:`~mvpa.clfs.gnb.GNB` implements Gaussian Naïve Bayes
>       Classifier.
>     - :func:`~mvpa.misc.fsl.base.read_fsl_design` to read FSL FEAT design.fsf
>       files (Contributed by Russell A. Poldrack).
>     - :class:`~mvpa.datasets.miscfx.SequenceStats` to provide basic
>       statistics on labels sequence (counter-balancing,
>       autocorrelation).
>     - New exceptions :class:`~mvpa.clfs.base.DegenerateInputError` and
>       :class:`~mvpa.clfs.base.FailedToTrainError` to be thrown by
>       classifiers primarily during training/testing.
>     - Debug target `STATMC` to report on progress of Monte-Carlo
>       sampling (during permutation testing).
> 
>   * Refactored (15 RF commits):
> 
>     - To get users prepared to 0.5 release, internally and in some
>       examples/documentation, access to states and
>       parameters is done via corresponding collections, not from the
>       top level object (e.g. `clf.states.predictions` instead of
>       soon-to-be-deprecated `clf.predictions`).  That should lead also
>       to improved performance.
>     - Adopted copy.py from python2.6 (support Ellipsis as well).
> 
>   * Fixed (38 BF commits):
> 
>     - GLM output does not depend on the enabled states any more.
>     - Variety of docstrings fixed and/or improved.
>     - Do not derive NaN scaling for SVM's C whenever data is
>       degenerate (lead to never finishing SVM training).
>     - :mod:`~mvpa.clfs.sg` :
> 
>       + KRR is optional now -- avoids crashing if KRR is not available.
>       + tolerance to absent `set_precompute_matrix` in svmlight in
>         recent shogun versions.
>       + support for recent (present in 0.9.1) API change in exposing
>         debug levels.
> 
>     - Python 2.4 compatibility issues: :class:`~mvpa.clfs.knn.kNN` and
>       :class:`~mvpa.featsel.ifs.IFS`
> 
> Enjoy!
> 
> 
> ------------------------------------------------------------------------
> 
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