[pymvpa] New release: PyMVPA 0.2.0

[Michael Hanke]

Hi,


let me announce a new shiny release of PyMVPA: 0.2.0. After a few months
of development we accumulated a nice changelog:


  * New Splitter class (HalfSplitter) to split into first and second half.
  * New Splitter class (CustomSplitter) to allow for splits with an arbitrary
    number of datasets per split and the ability to specify the association
    of samples with any of those datasets (not just the validation set).
  * New sparse multinomial logistic regression (SMLR) classifier and
    associated sensitivity analyzer.
  * New least angle regression classifier (LARS).
  * New gaussian process regression classifier (GPR).
  * Initial documentation on extending PyMVPA.
  * Switch to Sphinx for documentation handling.
  * New example comparing the performance of all classifiers on some
    artificial datasets.
  * New data mapper performing singular value decomposition (SVDMapper) and an
    example showing its usage.
  * More sophisticated data preprocessing: removal of non-linear trends and
    other arbitrary confounding regressors.
  * New `Harvester` class to feed data from arbitrary generators into multiple
    objects and store results of returned values and arbitrary properties.
  * Added documentation about how to build patched libsvm version with sane
    debug output.
  * libsvm bindings are not build by default anymore. Instructions on how to
    reenable them are available in the manual.
  * New wrapper from SVM implementation of the Shogun toolbox.
  * Important bugfix in RFE, which reported incorrect feature ids in some
    cases.
  * Added ability to compute stats/probabilities for all measures and transfer
    errors.


This release is by no means the end of something. It is more or less
(just) a milestone on the way to a fully featured framework. Be sure to
take a look at our nicely polished documentation (website, manual, ....) ;-)

http://pkg-exppsy.alioth.debian.org/pymvpa/

Cheers,

Michael

-- 
GPG key:  1024D/3144BE0F Michael Hanke
http://apsy.gse.uni-magdeburg.de/hanke
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