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Logo r-cran-rattle 2.6.26

by r-cran-robot - March 16, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 10941 views, 2386 downloads, 0 subscriptions

About: Graphical user interface for data mining in R

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:07.700426


Logo JMLR FastInf 1.0

by arielj - June 4, 2010, 14:04:37 CET [ Project Homepage BibTeX Download ] 10896 views, 3749 downloads, 1 subscription

About: The library is focused on implementation of propagation based approximate inference methods. Also implemented are a clique tree based exact inference, Gibbs sampling, and the mean field algorithm.

Changes:

Initial Announcement on mloss.org.


Logo Hivemall 0.3

by myui - March 13, 2015, 17:08:22 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10862 views, 1897 downloads, 3 subscriptions

About: Hivemall is a scalable machine learning library running on Hive/Hadoop.

Changes:
  • Supported Matrix Factorization
  • Added a support for TF-IDF computation
  • Supported AdaGrad/AdaDelta
  • Supported AdaGradRDA classification
  • Added normalization scheme

Logo libcmaes 0.9.5

by beniz - March 9, 2015, 09:05:22 CET [ Project Homepage BibTeX Download ] 10854 views, 2078 downloads, 3 subscriptions

About: Libcmaes is a multithreaded C++11 library (with Python bindings) for high performance blackbox stochastic optimization of difficult, possibly non-linear and non-convex functions, using the CMA-ES algorithm for Covariance Matrix Adaptation Evolution Strategy. Libcmaes is useful to minimize / maximize any function, without information regarding gradient or derivability.

Changes:

This is a major release, with several novelties, improvements and fixes, among which:

  • step-size two-point adaptaion scheme for improved performances in some settings, ref #88

  • important bug fixes to the ACM surrogate scheme, ref #57, #106

  • simple high-level workflow under Python, ref #116

  • improved performances in high dimensions, ref #97

  • improved profile likelihood and contour computations, including under geno/pheno transforms, ref #30, #31, #48

  • elitist mechanism for forcing best solutions during evolution, ref 103

  • new legacy plotting function, ref #110

  • optional initial function value, ref #100

  • improved C++ API, ref #89

  • Python bindings support with Anaconda, ref #111

  • configure script now tries to detect numpy when building Python bindings, ref #113

  • Python bindings now have embedded documentation, ref #114

  • support for Travis continuous integration, ref #122

  • lower resolution random seed initialization


Logo libstb 1.8

by wbuntine - April 24, 2014, 09:02:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10825 views, 2181 downloads, 1 subscription

About: Generalised Stirling Numbers for Pitman-Yor Processes: this library provides ways of computing generalised 2nd-order Stirling numbers for Pitman-Yor and Dirichlet processes. Included is a tester and parameter optimiser. This accompanies Buntine and Hutter's article: http://arxiv.org/abs/1007.0296, and a series of papers by Buntine and students at NICTA and ANU.

Changes:

Moved repository to GitHub, and added thread support to use the main table lookups in multi-threaded code.


Logo asp 0.3

by sonne - May 7, 2010, 10:25:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10809 views, 2129 downloads, 1 subscription

About: Accurate splice site predictor for a variety of genomes.

Changes:

Asp now supports three formats:

-g fname for gff format

-s fname for spf format

-b dir for a binary format compatible with mGene.

And a new switch

-t which switches on a sigmoid-based transformation of the svm scores to get scores between 0 and 1.


Logo Dependency modeling toolbox 0.2

by lml - April 30, 2010, 14:38:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10803 views, 1653 downloads, 1 subscription

About: Investigation of dependencies between multiple data sources allows the discovery of regularities and interactions that are not seen in individual data sets. The demand for such methods is increasing with the availability and size of co-occurring observations in computational biology, open data initiatives, and in other domains. We provide practical, open access implementations of general-purpose algorithms that help to realize the full potential of these information sources.

Changes:

Three independent modules (drCCA, pint, MultiWayCCA) have been added.


Logo bob 1.2.2

by anjos - October 28, 2013, 14:37:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10759 views, 2292 downloads, 1 subscription

About: Bob is a free signal-processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, in Switzerland.

Changes:

Bob 1.2.0 comes about 1 year after we released Bob 1.0.0. This new release comes with a big set of new features and lots of changes under the hood to make your experiments run even smoother. Some statistics:

Diff URL: https://github.com/idiap/bob/compare/v1.1.4...HEAD Commits: 629 Files changed: 954 Contributors: 7

Here is a quick list of things you should pay attention for while integrating your satellite packages against Bob 1.2.x:

  • The LBP module had its API changed look at the online docs for more details
  • LLRTrainer has been renamed to CGLogRegTrainer
  • The order in which you pass data to CGLogRegTrainer has been inverted (negatives now go first)
  • For C++ bindings, includes are in bob/python instead of bob/core/python
  • All specialized Bob exceptions are gone, if you were catching them, most have been cast into std::runtime_error's

For a detailed list of changes and additions, please look at our Changelog page for this release and minor updates:

https://github.com/idiap/bob/wiki/Changelog-from-1.1.4-to-1.2 https://github.com/idiap/bob/wiki/Changelog-from-1.2.0-to-1.2.1 https://github.com/idiap/bob/wiki/Changelog-from-1.2.1-to-1.2.2


Logo Harry 0.4.2

by konrad - April 16, 2016, 10:50:38 CET [ Project Homepage BibTeX Download ] 10624 views, 2291 downloads, 3 subscriptions

About: A Tool for Measuring String Similarity

Changes:

This release fixes the incorrect implementation of the bag distance.


About: This local and parallel computation toolbox is the Octave and Matlab implementation of several localized Gaussian process regression methods: the domain decomposition method (Park et al., 2011, DDM), partial independent conditional (Snelson and Ghahramani, 2007, PIC), localized probabilistic regression (Urtasun and Darrell, 2008, LPR), and bagging for Gaussian process regression (Chen and Ren, 2009, BGP). Most of the localized regression methods can be applied for general machine learning problems although DDM is only applicable for spatial datasets. In addition, the GPLP provides two parallel computation versions of the domain decomposition method. The easiness of being parallelized is one of the advantages of the localized regression, and the two parallel implementations will provide a good guidance about how to materialize this advantage as software.

Changes:

Initial Announcement on mloss.org.


Showing Items 151-160 of 628 on page 16 of 63: First Previous 11 12 13 14 15 16 17 18 19 20 21 Next Last