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Logo A Library for Online Streaming Feature Selection 1.0

by ykui713 - November 25, 2015, 13:23:01 CET [ BibTeX Download ] 91 views, 20 downloads, 0 subscriptions

About: LOFS is a software toolbox for online streaming feature selection


Initial Announcement on

Logo PyScriptClassifier 0.3.0

by cjb60 - November 25, 2015, 04:07:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 806 views, 214 downloads, 1 subscription

About: Easily prototype WEKA classifiers and filters using Python scripts.



  • Filters have now been implemented.
  • Classifier and filter classes satisfy base unit tests.


  • Can now choose to save the script in the model using the -save flag.


  • Added Python 3 support.
  • Added uses decorator to prevent non-essential arguments from being passed.
  • Fixed nasty bug where imputation, binarisation, and standardisation would not actually be applied to test instances.
  • GUI in WEKA now displays the exception as well.
  • Fixed bug where single quotes in attribute values could mess up args creation.
  • ArffToPickle now recognises class index option and arguments.
  • Fix nasty bug where filters were not being saved and were made from scratch from test data.


  • ArffToArgs gets temporary folder in a platform-independent way, instead of assuming /tmp/.
  • Can now save args in ArffToPickle using save.


  • Initial release.

Logo bandicoot 0.4

by yvesalexandre - November 20, 2015, 17:08:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 241 views, 42 downloads, 2 subscriptions

About: An open-source Python toolbox to analyze mobile phone metadata.


Initial Announcement on

Logo ADAMS 0.4.11

by fracpete - November 18, 2015, 10:58:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15315 views, 3077 downloads, 3 subscriptions

About: The Advanced Data mining And Machine learning System (ADAMS) is a novel, flexible workflow engine aimed at quickly building and maintaining real-world, complex knowledge workflows.


Some highlights of this release:

  • switch to Java 8
  • preferred IDE is now IntelliJ IDEA
  • removed OSX builds
  • 43 new actors
  • 13 new conversions
  • removed obsolete actors and conversions
  • added video support (video files and webcams)
  • added object detection and tracking (incl recording of object trails)
  • proof-of-concept remote-execution of jobs
  • SSH console
  • support for webscraping using JSoup
  • MEKA upgraded to 1.9.0
  • MOA regressor support added
  • better syntax highlighting for Groovy/Jython
  • several new Weka classifiers (eg Veto, LeanMultiScheme, ThresholdedBinaryClassification, InputSmearing)
  • new genetic algorithm: Hermione
  • extended the abstaining classifier framework (integrates with Weka)
  • adams-imaging split into: adams-imaging, adams-boofcv, adams-imagemagick, adams-imagej, adams-openimaj (newly added)

Logo Deep Semantic Ranking Based Hashing 1.0

by openpr_nlpr - November 18, 2015, 07:25:16 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 274 views, 70 downloads, 2 subscriptions

About: This algorithm is described in Deep Semantic Ranking Based Hashing for Multi-Label Image Retrieval. See


Initial Announcement on

Logo Hype 0.1.0

by gbaydin - November 16, 2015, 18:35:57 CET [ Project Homepage BibTeX Download ] 235 views, 36 downloads, 3 subscriptions

About: Hype is a proof-of-concept deep learning library, where you can perform optimization on compositional machine learning systems of many components, even when such components themselves internally perform optimization.


Initial Announcement on

Logo Armadillo library 6.200

by cu24gjf - November 15, 2015, 06:54:50 CET [ Project Homepage BibTeX Download ] 68483 views, 13974 downloads, 5 subscriptions

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About: Armadillo is a template C++ linear algebra library aiming towards a good balance between speed and ease of use, with a function syntax similar to MATLAB. Matrix decompositions are provided through optional integration with LAPACK, or one of its high performance drop-in replacements (eg. Intel MKL, OpenBLAS).

  • expanded diagmat() to handle non-square matrices and arbitrary diagonals
  • expanded trace() to handle non-square matrices
  • correction for datum::Z_0 constant
  • bug fixes for sparse eigen decomposition

About: Efficient and Flexible Distributed/Mobile Deep Learning Framework, for python, R, Julia and more


This version comes with Distributed and Mobile Examples

Logo Probabilistic Classification Vector Machine 0.22

by fmschleif - November 10, 2015, 13:16:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2907 views, 662 downloads, 3 subscriptions

About: PCVM library a c++/armadillo implementation of the Probabilistic Classification Vector Machine.


30.10.2015 * code has been revised in some places fixing also some errors different multiclass schemes and hdf5 file support added. Some speed ups and memory savings by better handling of intermediate objects.

27.05.2015: - Matlab binding under Windows available. Added a solution file for VS'2013 express to compile a matlab mex binding. Can not yet confirm that under windows the code is really using multiple cores (under linux it does)

29.04.2015 * added an implementation of the Nystroem based PCVM includes: Nystroem based singular value decomposition (SVD), eigenvalue decomposition (EVD) and pseudo-inverse calculation (PINV)

22.04.2015 * implementation of the PCVM released

Logo Apache Mahout 0.11.1

by gsingers - November 9, 2015, 16:12:06 CET [ Project Homepage BibTeX Download ] 18840 views, 4955 downloads, 3 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 [...]


Apache Mahout introduces a new math environment we call Samsara, for its theme of universal renewal. It reflects a fundamental rethinking of how scalable machine learning algorithms are built and customized. Mahout-Samsara is here to help people create their own math while providing some off-the-shelf algorithm implementations. At its core are general linear algebra and statistical operations along with the data structures to support them. You can use is as a library or customize it in Scala with Mahout-specific extensions that look something like R. Mahout-Samsara comes with an interactive shell that runs distributed operations on a Spark cluster. This make prototyping or task submission much easier and allows users to customize algorithms with a whole new degree of freedom. Mahout Algorithms include many new implementations built for speed on Mahout-Samsara. They run on Spark 1.3+ and some on H2O, which means as much as a 10x speed increase. You’ll find robust matrix decomposition algorithms as well as a Naive Bayes classifier and collaborative filtering. The new spark-itemsimilarity enables the next generation of cooccurrence recommenders that can use entire user click streams and context in making recommendations.

Showing Items 1-10 of 604 on page 1 of 61: 1 2 3 4 5 6 Next Last