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Logo Apache Mahout 0.8

by gsingers - July 27, 2013, 15:52:32 CET [ Project Homepage BibTeX Download ] 15466 views, 4262 downloads, 2 subscriptions

About: Apache Mahout is an Apache Software Foundation project with the goal of creating both a community of users and a scalable, Java-based framework consisting of many machine learning algorithm [...]

Changes:

Apache Mahout 0.8 contains, amongst a variety of performance improvements and bug fixes, an implementation of Streaming K-Means, deeper Lucene/Solr integration and new scalable recommender algorithms. For a full description of the newest release, see http://mahout.apache.org/.


Logo JMLR PyBrain 0.3

by bayerj - March 3, 2010, 15:00:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15394 views, 1752 downloads, 2 subscriptions

About: PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easy-to-use yet still powerful algorithms for machine learning tasks, including a variety of predefined [...]

Changes:
  • more documentation, including new tutorials
  • new and updated example scripts
  • major restructuring of the reinforcement learning part
  • homogeneous interface for optimization algorithms
  • fast networks (arac) are now in an independent package
  • new algorithms, network structures, tools...

Logo gensim 0.8.6

by Radim - December 9, 2012, 13:15:16 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15350 views, 3216 downloads, 1 subscription

About: Python Framework for Vector Space Modelling that can handle unlimited datasets (streamed input, online algorithms work incrementally in constant memory).

Changes:
  • added the "hashing trick" (by Homer Strong)
  • support for adding target classes in SVMlight format (by Corrado Monti)
  • fixed problems with global lemmatizer object when running in parallel on Windows
  • parallelization of Wikipedia processing + added script version that lemmatizes the input documents
  • added class method to initialize Dictionary from an existing corpus (by Marko Burjek)

Logo r-cran-penalized 0.9-42

by r-cran-robot - November 6, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 15119 views, 3429 downloads, 1 subscription

About: L1 (lasso and fused lasso) and L2 (ridge) penalized estimation in GLMs and in the Cox model

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:06.939105


Logo r-cran-arules 1.1-5

by r-cran-robot - August 19, 2014, 00:00:00 CET [ Project Homepage BibTeX Download ] 15067 views, 3100 downloads, 3 subscriptions

About: Mining Association Rules and Frequent Itemsets

Changes:

Fetched by r-cran-robot on 2014-11-01 00:00:04.179280


Logo mloss.org svn-r645-Mar-2011

by sonne - March 23, 2011, 11:09:18 CET [ Project Homepage BibTeX Download ] 14850 views, 2061 downloads, 1 subscription

About: This is the source code of the mloss.org website.

Changes:

Now works with newer django versions and fixes several warnings and minor bugs underneath. The only user visible change is probably that the subscription and bookmark buttons work again.


Logo JMLR GPstuff 4.5

by avehtari - July 22, 2014, 14:03:11 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14505 views, 3576 downloads, 2 subscriptions

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About: The GPstuff toolbox is a versatile collection of Gaussian process models and computational tools required for inference. The tools include, among others, various inference methods, sparse approximations and model assessment methods.

Changes:

2014-07-22 Version 4.5

New features

  • Input dependent noise and signal variance.

    • Tolvanen, V., Jylänki, P. and Vehtari, A. (2014). Expectation Propagation for Nonstationary Heteroscedastic Gaussian Process Regression. In Proceedings of IEEE International Workshop on Machine Learning for Signal Processing, accepted for publication. Preprint http://arxiv.org/abs/1404.5443
  • Sparse stochastic variational inference model.

    • Hensman, J., Fusi, N. and Lawrence, N. D. (2013). Gaussian processes for big data. arXiv preprint http://arxiv.org/abs/1309.6835.
  • Option 'autoscale' in the gp_rnd.m to get split normal approximated samples from the posterior predictive distribution of the latent variable.

    • Geweke, J. (1989). Bayesian Inference in Econometric Models Using Monte Carlo Integration. Econometrica, 57(6):1317-1339.

    • Villani, M. and Larsson, R. (2006). The Multivariate Split Normal Distribution and Asymmetric Principal Components Analysis. Communications in Statistics - Theory and Methods, 35(6):1123-1140.

Improvements

  • New unit test environment using the Matlab built-in test framework (the old Xunit package is still also supported).
  • Precomputed demo results (including the figures) are now available in the folder tests/realValues.
  • New demos demonstrating new features etc.
    • demo_epinf, demonstrating the input dependent noise and signal variance model
    • demo_svi_regression, demo_svi_classification
    • demo_modelcomparison2, demo_survival_comparison

Several minor bugfixes


Logo JMLR CARP 3.3

by volmeln - November 7, 2013, 15:48:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14495 views, 4628 downloads, 1 subscription

About: CARP: The Clustering Algorithms’ Referee Package

Changes:

Generalized overlap error and some bugs have been fixed


Logo r-cran-GAMBoost 1.2-2

by r-cran-robot - April 1, 2013, 00:00:04 CET [ Project Homepage BibTeX Download ] 14432 views, 2721 downloads, 1 subscription

About: Generalized linear and additive models by likelihood based boosting

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:04.893311


Logo The Infinite Hidden Markov Model 0.5

by jvangael - July 21, 2010, 23:41:24 CET [ BibTeX BibTeX for corresponding Paper Download ] 14358 views, 2536 downloads, 1 subscription

About: An implementation of the infinite hidden Markov model.

Changes:

Since 0.4: Removed dependency from lightspeed (now using statistics toolbox). Updated to newer matlab versions.


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