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Showing Items 91-100 of 652 on page 10 of 66: First Previous 5 6 7 8 9 10 11 12 13 14 15 Next Last

About: This local and parallel computation toolbox is the Octave and Matlab implementation of several localized Gaussian process regression methods: the domain decomposition method (Park et al., 2011, DDM), partial independent conditional (Snelson and Ghahramani, 2007, PIC), localized probabilistic regression (Urtasun and Darrell, 2008, LPR), and bagging for Gaussian process regression (Chen and Ren, 2009, BGP). Most of the localized regression methods can be applied for general machine learning problems although DDM is only applicable for spatial datasets. In addition, the GPLP provides two parallel computation versions of the domain decomposition method. The easiness of being parallelized is one of the advantages of the localized regression, and the two parallel implementations will provide a good guidance about how to materialize this advantage as software.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-ipred 0.9-1

by r-cran-robot - November 14, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 17496 views, 4016 downloads, 1 subscription

About: Improved Predictors

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:05.613011


Logo Maja Machine Learning Framework 1.0

by jhm - September 13, 2011, 15:13:56 CET [ Project Homepage BibTeX Download ] 19497 views, 3998 downloads, 1 subscription

About: The Maja Machine Learning Framework (MMLF) is a general framework for problems in the domain of Reinforcement Learning (RL) written in python. It provides a set of RL related algorithms and a set of benchmark domains. Furthermore it is easily extensible and allows to automate benchmarking of different agents.

Changes:
  • Experiments can now be invoked from the command line
  • Experiments can now be "scripted"
  • MMLF Experimenter contains now basic module for statistical hypothesis testing
  • MMLF Explorer can now visualize the model that has been learned by an agent

Logo r-cran-GAMBoost 1.2-2

by r-cran-robot - April 1, 2013, 00:00:04 CET [ Project Homepage BibTeX Download ] 20729 views, 3978 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 r-cran-randomForest 4.6-7

by r-cran-robot - October 16, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 19625 views, 3960 downloads, 1 subscription

About: Breiman and Cutler's random forests for classification and regression

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:07.638240


Logo The Infinite Hidden Markov Model 0.5

by jvangael - July 21, 2010, 23:41:24 CET [ BibTeX BibTeX for corresponding Paper Download ] 23257 views, 3955 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.


Logo Orange 2.6

by janez - February 14, 2013, 18:15:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 21190 views, 3949 downloads, 1 subscription

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About: Orange is a component-based machine learning and data mining software. It includes a friendly yet powerful and flexible graphical user interface for visual programming. For more advanced use(r)s, [...]

Changes:

The core of the system (except the GUI) no longer includes any GPL code and can be licensed under the terms of BSD upon request. The graphical part remains under GPL.

Changed the BibTeX reference to the paper recently published in JMLR MLOSS.


Logo BCPy2000 17374

by jez - July 8, 2010, 22:11:24 CET [ Project Homepage BibTeX Download ] 21441 views, 3949 downloads, 1 subscription

About: BCPy2000 provides a platform for rapid, flexible development of experimental Brain-Computer Interface systems based on the BCI2000.org project. From the developer's point of view, the implementation [...]

Changes:

Bugfixes and tuneups, and an expanded set of (some more-, some less-documented, optional tools)


Logo KeLP 2.2.1

by kelpadmin - August 7, 2017, 17:20:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 18531 views, 3918 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 cache (FixSizeKernelCache) that can store a larger number of computations.

  • Evaluators for measuring the quality of Clustering algorithms.

Furthermore we also released the new module kelp-input-generator, that contains the facilities to parse text snippets and generate tree representations for 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 2.2.1!


Logo r-cran-tgp 2.4-3

by r-cran-robot - December 18, 2011, 00:00:00 CET [ Project Homepage BibTeX Download ] 19122 views, 3883 downloads, 1 subscription

About: Bayesian treed Gaussian process models

Changes:

Fetched by r-cran-robot on 2012-02-01 00:00:11.834310


Showing Items 91-100 of 652 on page 10 of 66: First Previous 5 6 7 8 9 10 11 12 13 14 15 Next Last