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Logo gensim 0.8.6

by Radim - December 9, 2012, 13:15:16 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15670 views, 3275 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 Apache Mahout 0.8

by gsingers - July 27, 2013, 15:52:32 CET [ Project Homepage BibTeX Download ] 15661 views, 4301 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 r-cran-arules 1.1-5

by r-cran-robot - August 19, 2014, 00:00:00 CET [ Project Homepage BibTeX Download ] 15579 views, 3233 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 JMLR PyBrain 0.3

by bayerj - March 3, 2010, 15:00:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15559 views, 1776 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 JMLR GPstuff 4.5

by avehtari - July 22, 2014, 14:03:11 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15468 views, 3726 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 r-cran-penalized 0.9-42

by r-cran-robot - November 6, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 15403 views, 3515 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 mloss.org svn-r645-Mar-2011

by sonne - March 23, 2011, 11:09:18 CET [ Project Homepage BibTeX Download ] 15000 views, 2082 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 CARP 3.3

by volmeln - November 7, 2013, 15:48:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14803 views, 4734 downloads, 1 subscription

About: CARP: The Clustering Algorithms’ Referee Package

Changes:

Generalized overlap error and some bugs have been fixed


Logo JMLR Jstacs 2.1

by keili - June 3, 2013, 07:32:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14615 views, 3475 downloads, 2 subscriptions

About: A Java framework for statistical analysis and classification of biological sequences

Changes:

New classes:

  • MultipleIterationsCondition: Requires another TerminationCondition to fail a contiguous, specified number of times
  • ClassifierFactory: Allows for creating standard classifiers
  • SeqLogoPlotter: Plot PNG sequence logos from within Jstacs
  • MultivariateGaussianEmission: Multivariate Gaussian emission density for a Hidden Markov Model
  • MEManager: Maximum entropy model

New features and improvements:

  • Alignment: Added free shift alignment
  • PerformanceMeasure and sub-classes: Extension to weighted test data
  • AbstractClassifier, ClassifierAssessment and sub-classes: Adaption to weighted PerformanceMeasures
  • DNAAlphabet: Parser speed-up
  • PFMComparator: Extension to PFM from other sources/databases
  • ToolBox: New convenience methods for computing several statistics (e.g., median, correlation)
  • SignificantMotifOccurrencesFinder: New methods for computing PWMs and statistics from predictions
  • SequenceScore and sub-classes: New method toString(NumberFormat)
  • DataSet: Adaption to weighted data, e.g., partitioning
  • REnvironment: Changed several methods from String to CharSequence

Restructuring:

  • changed MultiDimensionalSequenceWrapperDiffSM to MultiDimensionalSequenceWrapperDiffSS

Several minor new features, bug fixes, and code cleanups


Logo r-cran-GAMBoost 1.2-2

by r-cran-robot - April 1, 2013, 00:00:04 CET [ Project Homepage BibTeX Download ] 14574 views, 2751 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


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