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Logo r-cran-CoxBoost 1.4

by r-cran-robot - October 1, 2016, 00:00:04 CET [ Project Homepage BibTeX Download ] 28469 views, 5580 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 2016-10-01 00:00:04.178988


Logo r-cran-e1071 1.6-7

by r-cran-robot - October 1, 2016, 00:00:04 CET [ Project Homepage BibTeX Download ] 29232 views, 6081 downloads, 3 subscriptions

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

Changes:

Fetched by r-cran-robot on 2016-10-01 00:00:04.307859


Logo r-cran-Boruta 5.1.0

by r-cran-robot - October 1, 2016, 00:00:03 CET [ Project Homepage BibTeX Download ] 19680 views, 4124 downloads, 2 subscriptions

About: Wrapper Algorithm for All Relevant Feature Selection

Changes:

Fetched by r-cran-robot on 2016-10-01 00:00:03.742650


Logo Somoclu 1.7.0

by peterwittek - September 30, 2016, 15:08:49 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 18565 views, 3474 downloads, 3 subscriptions

About: Somoclu is a massively parallel implementation of self-organizing maps. It relies on OpenMP for multicore execution, MPI for distributing the workload, and it can be accelerated by CUDA on a GPU cluster. A sparse kernel is also included, which is useful for training maps on vector spaces generated in text mining processes. Apart from a command line interface, Python, Julia, R, and MATLAB are supported.

Changes:
  • New: Julia interface is available (https://github.com/peterwittek/Somoclu.jl).
  • New: Method get_surface_state of the Somoclu object in Python calculates the activation map for all data instances.
  • New: Method view_activation_map of the Somoclu object in Python allows plotting the activation map for the training data instances or for a new data instance.
  • New: Method view_similarity_matrix of the Somoclu object in Python visualizes the similarity matrix of data points according to their distance to the nodes in the map.
  • Fixed: CRAN-friendliness improved.

Logo RLScore 0.7

by aatapa - September 20, 2016, 09:51:25 CET [ Project Homepage BibTeX Download ] 326 views, 43 downloads, 2 subscriptions

About: RLScore - regularized least-squares machine learning algorithms package

Changes:

Initial Announcement on mloss.org.


Logo r-cran-bst 0.3-14

by r-cran-robot - September 12, 2016, 00:00:00 CET [ Project Homepage BibTeX Download ] 5481 views, 1317 downloads, 0 subscriptions

About: Gradient Boosting

Changes:

Fetched by r-cran-robot on 2016-10-01 00:00:03.810300


Logo slim for matlab 0.2

by ustunb - August 23, 2016, 20:27:00 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1066 views, 147 downloads, 2 subscriptions

About: learn optimized scoring systems using MATLAB and the CPLEX Optimization Studio

Changes:

Initial Announcement on mloss.org.


Logo NaN toolbox 3.0.3

by schloegl - August 19, 2016, 11:08:57 CET [ Project Homepage BibTeX Download ] 50240 views, 10102 downloads, 3 subscriptions

About: NaN-toolbox is a statistics and machine learning toolbox for handling data with and without missing values.

Changes:

Changes in v.3.0.3 - improve compatibility for Octave on Windows

Changes in v.3.0.1 - fix packaging for octave

Changes in v.2.8.5 - bug fix: trimmean - compiler support for gcc-5 and clang - fix typos

For details see the CHANGELOG at http://pub.ist.ac.at/~schloegl/matlab/NaN/CHANGELOG


Logo JMLR dlib ml 19.1

by davis685 - August 13, 2016, 20:24:13 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 154077 views, 24901 downloads, 5 subscriptions

About: This project is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.

Changes:

This release adds support for cuDNN 5.1 as well as a number of minor bug fixes and usability improvements.


Logo KeLP 2.1.0

by kelpadmin - August 11, 2016, 10:40:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10680 views, 2472 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 flexible system to manipulate example-pairs
  • new manipulators for performing tree pruning
  • new examples for the usage of 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 2.1.0!


Showing Items 1-10 of 624 on page 1 of 63: 1 2 3 4 5 6 Next Last