[mlpack] mlpack 1.0.9 released

[Thuener Silva]

Great news Ryan!

How to uninstall the previous version of mlpack?

Grats,
Thuener


On Mon, Jul 28, 2014 at 3:30 PM, Ryan Curtin <gth671b at mail.gatech.edu>
wrote:

> Hello there,
>
> Today the last bits of work required for a new mlpack release were
> finished.  You can download mlpack 1.0.9 from
>
>   http://www.mlpack.org/
>
> with a direct URL
>
>   http://www.mlpack.org/files/mlpack-1.0.9.tar.gz
>
> It has been a while since a release, and there have been a lot of
> contributions.  The projects from our five Summer of Code students are
> starting to come to a close, and some of their code has been
> incorporated into this release.  (You can expect another release shortly
> after their projects are done; hopefully early September.)
>
> Here is a list of changes, pulled straight from HISTORY.txt:
>
>  - GMM initialization is now safer and provides a working GMM when
>    constructed with only the dimensionality and number of Gaussians
>    (#314).
>
>  - Check for division by 0 in Forward-Backward Algorithm in HMMs (#314).
>
>  - Fix MaxVarianceNewCluster (used when re-initializing clusters for
>    k-means) (#314).
>
>  - Fixed implementation of Viterbi algorithm in HMM::Predict() (#316).
>
>  - Significant speedups for dual-tree algorithms using the cover tree
>    (#243, #329) including a faster implementation of FastMKS.
>
>  - Fix for LRSDP optimizer so that it compiles and can be used (#325).
>
>  - CF (collaborative filtering) now expects users and items to be
>    zero-indexed, not one-indexed (#324).
>
>  - CF::GetRecommendations() API change: now requires the number of
>    recommendations as the first parameter.  The number of users in the
>    local neighborhood should be specified with
>    CF::NumUsersForSimilarity().
>
>  - Removed incorrect PeriodicHRectBound (#30).
>
>  - Refactor LRSDP into LRSDP class and standalone function to be
>    optimized (#318).
>
>  - Fix for centering in kernel PCA (#355).
>
>  - Added simulated annealing (SA) optimizer, contributed by Zhihao Lou.
>
>  - HMMs now support initial state probabilities; these can be set in the
>    constructor, trained, or set manually with HMM::Initial() (#315).
>
>  - Added Nyström method for kernel matrix approximation by Marcus Edel.
>
>  - Kernel PCA now supports using Nyström method for approximation.
>
>  - Ball trees now work with dual-tree algorithms, via the BallBound<>
>    bound structure (#320); fixed by Yash Vadalia.
>
>  - The NMF class is now AMF<>, and supports far more types of
>    factorizations, by Sumedh Ghaisas.
>
>  - A QUIC-SVD implementation has returned, written by Siddharth Agrawal
>    and based on older code from Mudit Gupta.
>
>  - Added perceptron and decision stump by Udit Saxena (these are weak
>    learners for an eventual AdaBoost class).
>
>  - Sparse autoencoder added by Siddharth Agrawal.
>
> If you want a (nearly) full list of bugfixes and changes since 1.0.8,
> you can see the list of resolved tickets:
>
>
> http://www.mlpack.org/trac/query?status=closed&group=resolution&milestone=mlpack+1.0.9
> (Note: at the moment, Trac is down.  Sorry about that.  It is being
> worked on, but there is no solution quite yet... it should be back up in
> a day or two.)
>
> The benchmarks for 1.0.9 are not done yet, but I will respond to this
> email with a link when they are complete and posted.
>
> The next release is likely to be 1.1.0; we are anticipating that there
> will be some API reverse compatibility breakage.  However, we will
> provide a guide on any big changes and how code can be adapted.  Many of
> the abstractions we use to organize and understand our algorithms are
> still not completely stable (especially the tree API), and sometimes
> this forces changes...
>
> Anyway, thanks to everyone for their hard work on this release!  Lots of
> work has gone into this one.
>
> Ryan
>
> --
> Ryan Curtin    | "This is how Number One works!"
> ryan at ratml.org |   - Number One
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> mlpack at cc.gatech.edu
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>
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