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Logo DynaML 1.4.1

by mandar2812 - April 20, 2017, 18:32:33 CET [ Project Homepage BibTeX Download ] 237 views, 30 downloads, 1 subscription

About: DynaML is a Scala environment for conducting research and education in Machine Learning. DynaML comes packaged with a powerful library of classes implementing predictive models and a Scala REPL where one can not only build custom models but also play around with data work-flows.

Changes:

Initial Announcement on mloss.org.


Logo pycobra regression analysis and ensemble toolkit 0.1.0

by bhargavvader - April 19, 2017, 15:04:14 CET [ Project Homepage BibTeX Download ] 232 views, 28 downloads, 2 subscriptions

About: pycobra is a python toolkit to help with regression analysis and visualisation. It provides an implementation of the COBRA predictor aggregation algorithm.

Changes:

Initial Announcement on mloss.org.


Logo JMLR MLPACK 2.2.1

by rcurtin - April 13, 2017, 22:25:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 77126 views, 13655 downloads, 6 subscriptions

Rating Whole StarWhole StarWhole StarWhole Star1/2 Star
(based on 1 vote)

About: A scalable, fast C++ machine learning library, with emphasis on usability.

Changes:

Released Apr. 13th, 2016.

  • Compilation fix for mlpack_nca and mlpack_test on older Armadillo versions (#984).

Logo Theano 0.9.0

by jaberg - April 10, 2017, 20:30:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 31400 views, 5287 downloads, 3 subscriptions

About: A Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Dynamically generates CPU and GPU modules for good performance. Deep Learning Tutorials illustrate deep learning with Theano.

Changes:

Theano 0.9.0 (20th of March, 2017)

Highlights (since 0.8.0):

* Better Python 3.5 support
* Better numpy 1.12 support
* Conda packages for Mac, Linux and Windows
* Support newer Mac and Windows versions
* More Windows integration:

    * Theano scripts (``theano-cache`` and ``theano-nose``) now works on Windows
    * Better support for Windows end-lines into C codes
    * Support for space in paths on Windows

* Scan improvements:

    * More scan optimizations, with faster compilation and gradient computation
    * Support for checkpoint in scan (trade off between speed and memory usage, useful for long sequences)
    * Fixed broadcast checking in scan

* Graphs improvements:

    * More numerical stability by default for some graphs
    * Better handling of corner cases for theano functions and graph optimizations
    * More graph optimizations with faster compilation and execution
    * smaller and more readable graph

* New GPU back-end:

    * Removed warp-synchronous programming to get good results with newer CUDA drivers
    * More pooling support on GPU when cuDNN isn't available
    * Full support of ignore_border option for pooling
    * Inplace storage for shared variables
    * float16 storage
    * Using PCI bus ID of graphic cards for a better mapping between theano device number and nvidia-smi number
    * Fixed offset error in ``GpuIncSubtensor``

* Less C code compilation
* Added support for bool dtype
* Updated and more complete documentation
* Bug fixes related to merge optimizer and shape inference
* Lot of other bug fixes, crashes fixes and warning improvements

Logo Calibrated AdaMEC 1.0

by nnikolaou - April 8, 2017, 13:57:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 544 views, 64 downloads, 2 subscriptions

About: Code for Calibrated AdaMEC for binary cost-sensitive classification. The method is just AdaBoost that properly calibrates its probability estimates and uses a cost-sensitive (i.e. risk-minimizing) decision threshold to classify new data.

Changes:

Initial Announcement on mloss.org.


Logo KeLP 2.2.0

by kelpadmin - April 7, 2017, 16:51:42 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14256 views, 3156 downloads, 3 subscriptions

About: Kernel-based Learning Platform (KeLP) is Java framework that supports the implementation of kernel-based learning algorithms, as well as an agile definition of kernel functions over generic data representation, e.g. vectorial data or discrete structures. The framework has been designed to decouple kernel functions and learning algorithms, through the definition of specific interfaces. Once a new kernel function has been implemented, it can be automatically adopted in all the available kernel-machine algorithms. KeLP includes different Online and Batch Learning algorithms for Classification, Regression and Clustering, as well as several Kernel functions, ranging from vector-based to structural kernels. It allows to build complex kernel machine based systems, leveraging on JSON/XML interfaces to instantiate prediction models without writing a single line of code.

Changes:

In addition to minor bug fixes, this release includes:

  • A new learning algorithm that enable (for the first time in KeLP) to deal with sequences labeling problems! It is based on a Markovian formulation within a SVM framework. Most noticeably: this new meta-algorithm for sequence learning can deal both with linear algorithms and with kernel-based algorithms!

  • A new cache (SimpleDynamicKernelCache) has been added to avoid the need of specifying the number of expected items in the dataset. It is not specialized for any learning algorithm, so it is not the most efficient cache, but it is very easy to use.

Furthermore we also released a brand new web site www.kelp-ml.org, where you can find several tutorials and documentation about KeLP!

Check out this new version from our repositories. API Javadoc is already available. Your suggestions will be very precious for us, so download and try KeLP 2.2.0!


Logo r-cran-CoxBoost 1.4

by r-cran-robot - April 1, 2017, 00:00:04 CET [ Project Homepage BibTeX Download ] 32900 views, 6261 downloads, 3 subscriptions

About: Cox models by likelihood based boosting for a single survival endpoint or competing risks

Changes:

Fetched by r-cran-robot on 2017-04-01 00:00:04.728359


Logo r-cran-e1071 1.6-8

by r-cran-robot - April 1, 2017, 00:00:04 CET [ Project Homepage BibTeX Download ] 36190 views, 7251 downloads, 3 subscriptions

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(based on 1 vote)

About: Misc Functions of the Department of Statistics, Probability Theory Group (Formerly

Changes:

Fetched by r-cran-robot on 2017-04-01 00:00:04.887707


Logo r-cran-Boruta 5.2.0

by r-cran-robot - April 1, 2017, 00:00:03 CET [ Project Homepage BibTeX Download ] 24923 views, 5046 downloads, 2 subscriptions

About: Wrapper Algorithm for All Relevant Feature Selection

Changes:

Fetched by r-cran-robot on 2017-04-01 00:00:03.778215


Logo r-cran-CORElearn 1.50.3

by r-cran-robot - March 28, 2017, 00:00:00 CET [ Project Homepage BibTeX Download ] 16872 views, 3558 downloads, 2 subscriptions

About: Classification, Regression and Feature Evaluation

Changes:

Fetched by r-cran-robot on 2017-04-01 00:00:04.175765


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