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Logo JMLR dlib ml 18.12

by davis685 - December 20, 2014, 22:38:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 87923 views, 15210 downloads, 2 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 tools for computing 2D FFTs, Hough transforms, image skeletonizations, and also a simple and type safe API for calling C++ code from MATLAB.


Logo WEKA 3.7.12

by mhall - December 17, 2014, 03:04:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 41700 views, 6163 downloads, 2 subscriptions

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About: The Weka workbench contains a collection of visualization tools and algorithms for data analysis and predictive modelling, together with graphical user interfaces for easy access to this [...]

Changes:

In core weka:

  • GUIChooser now has a plugin exension point that allows implementations of GUIChooser.GUIChooserMenuPlugin to appear as entries in either the Tools or Visualization menus
  • SubsetByExpression filter now has support for regexp matching
  • weka.classifiers.IterativeClassifierOptimizer - a classifier that can efficiently optimize the number of iterations for a base classifier that implements IterativeClassifier
  • Speedup for LogitBoost in the two class case
  • weka.filters.supervised.instance.ClassBalancer - a simple filter to balance the weight of classes
  • New class hierarchy for stopwords algorithms. Includes new methods to read custom stopwords from a file and apply multiple stopwords algorithms
  • Ability to turn off capabilities checking in Weka algorithms. Improves runtime for ensemble methods that create a lot of simple base classifiers
  • Memory savings in weka.core.Attribute
  • Improvements in runtime for SimpleKMeans and EM
  • weka.estimators.UnivariateMixtureEstimator - new mixture estimator

In packages:

  • New discriminantAnalysis package. Provides an implementation of Fisher's linear discriminant analysis
  • Quartile estimators, correlation matrix heat map and k-means++ clustering in distributed Weka
  • Support for default settings for GridSearch via a properties file
  • Improvements in scripting with addition of the offical Groovy console (kfGroovy package) from the Groovy project and TigerJython (new tigerjython package) as the Jython console via the GUIChooser
  • Support for the latest version of MLR in the RPlugin package
  • EAR4 package contributed by Vahid Jalali
  • StudentFilters package contributed by Chris Gearhart
  • graphgram package contributed by Johannes Schneider

Logo Accord.NET Framework 2.14.0

by cesarsouza - December 9, 2014, 23:04:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 16998 views, 3454 downloads, 2 subscriptions

About: The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and an extensive online documentation helps fill in the details.

Changes:

Adding a large number of new distributions, such as Anderson-Daring, Shapiro-Wilk, Inverse Chi-Square, Lévy, Folded Normal, Shifted Log-Logistic, Kumaraswamy, Trapezoidal, U-quadratic and BetaPrime distributions, Birnbaum-Saunders, Generalized Normal, Gumbel, Power Lognormal, Power Normal, Triangular, Tukey Lambda, Logistic, Hyperbolic Secant, Degenerate and General Continuous distributions.

Other additions include new statistical hypothesis tests such as Anderson-Daring and Shapiro-Wilk; as well as support for all of LIBLINEAR's support vector machine algorithms; and format reading support for MATLAB/Octave matrices, LibSVM models, sparse LibSVM data files, and many others.

For a complete list of changes, please see the full release notes at the release details page at:

https://github.com/accord-net/framework/releases


About: a parallel LDA learning toolbox in Multi-Core Systems for big topic modeling.

Changes:

Initial Announcement on mloss.org.


Logo Armadillo library 4.550

by cu24gjf - December 5, 2014, 03:24:54 CET [ Project Homepage BibTeX Download ] 48105 views, 10332 downloads, 4 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).

Changes:
  • added matrix exponential function: expmat()
  • faster .log_p() and .avg_log_p() functions in the Gaussian mixture model class
  • faster handling of in-place addition/subtraction of expressions with an outer product
  • workaround for a bug in GCC 4.4

Logo linearizedGP 1.0

by dsteinberg - November 28, 2014, 07:02:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 304 views, 48 downloads, 1 subscription

About: Gaussian processes with general nonlinear likelihoods using the unscented transform or Taylor series linearisation.

Changes:

Initial Announcement on mloss.org.


Logo OpenNN 1.0

by Sergiointelnics - November 21, 2014, 13:15:47 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 646 views, 111 downloads, 3 subscriptions

About: OpenNN is an open source class library written in C++ which implements neural networks. The library has been designed to learn from both data sets and mathematical models.

Changes:

Initial Announcement on mloss.org.


Logo JMLR Sally 0.9.2

by konrad - November 19, 2014, 20:28:35 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 22235 views, 4486 downloads, 3 subscriptions

About: A Tool for Embedding Strings in Vector Spaces

Changes:

Fixed severe bug in concurrent computation of blended n-grams.


Logo Harry 0.3.2

by konrad - November 19, 2014, 20:24:21 CET [ Project Homepage BibTeX Download ] 2789 views, 603 downloads, 2 subscriptions

About: A Tool for Measuring String Similarity

Changes:

Several minor bugfixes.


Logo libcmaes 0.9.3

by beniz - November 17, 2014, 14:04:10 CET [ Project Homepage BibTeX Download ] 2842 views, 594 downloads, 3 subscriptions

About: Libcmaes is a multithreaded C++11 library (with Python bindings) for high performance blackbox stochastic optimization of difficult, possibly non-linear and non-convex functions, using the CMA-ES algorithm for Covariance Matrix Adaptation Evolution Strategy. Libcmaes is useful to minimize / maximize any function, without information regarding gradient or derivability.

Changes:

This is an important update:

  • full support for surrogates, allowing optimization of costly objective functions, ref #57

  • integrated rankign SVM default surrogate, ref #83

  • Python bindings for surrogates, ref #75

  • more informed optimization status and error messages, ref #85

  • API for computing confidence intervals around optima, ref #30

  • API for computing 2D contour around optima, ref #31

  • new 'elitist' scheme for improved restart strategy useful on some rather difficult functions, ref #77

  • fixed Eigen namespace import, ref #62

  • fixed and added new parameter vector getter in Candidate, ref #84


Logo Lua MapReduce v0.3.6

by pakozm - November 15, 2014, 13:20:01 CET [ Project Homepage BibTeX Download ] 2101 views, 451 downloads, 3 subscriptions

About: Lua-MapReduce framework implemented in Lua using luamongo driver and MongoDB as storage. It follows Iterative MapReduce for training of Machine Learning statistical models.

Changes:
  • Improved tuple implementation.

Logo Hub Miner 1.0

by nenadtomasev - November 12, 2014, 19:41:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 459 views, 81 downloads, 1 subscription

About: Hubness-aware Machine Learning for High-dimensional Data

Changes:

Initial Announcement on mloss.org.


Logo libcluster 2.1

by dsteinberg - October 31, 2014, 23:27:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 492 views, 93 downloads, 2 subscriptions

About: An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.

Changes:

Initial Announcement on mloss.org.


Logo LogRegCrowds, Logistic Regression from Crowds 1.0

by fmpr - October 30, 2014, 19:10:23 CET [ Project Homepage BibTeX Download ] 393 views, 94 downloads, 2 subscriptions

About: LogReg-Crowds is a collection of Julia implementations of various approaches for learning a logistic regression model multiple annotators and crowds, namely the works of Raykar et al. (2010), Rodrigues et al. (2013) and Dawid and Skene (1979).

Changes:

Initial Announcement on mloss.org.


About: This library implements the Optimum-Path Forest classifier for unsupervised and supervised learning.

Changes:

Initial Announcement on mloss.org.


Logo pySPACE 1.2

by krell84 - October 29, 2014, 15:36:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2335 views, 491 downloads, 1 subscription

About: pySPACE is the abbreviation for "Signal Processing and Classification Environment in Python using YAML and supporting parallelization". It is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface.

Changes:

improved testing, improved documentation, windows compatibility, more algorithms


Logo BayesOpt, a Bayesian Optimization toolbox 0.7.2

by rmcantin - October 10, 2014, 19:12:59 CET [ Project Homepage BibTeX Download ] 9885 views, 2024 downloads, 4 subscriptions

About: BayesOpt is an efficient, C++ implementation of the Bayesian optimization methodology for nonlinear-optimization, experimental design and stochastic bandits. In the literature it is also called Sequential Kriging Optimization (SKO) or Efficient Global Optimization (EGO). There are also interfaces for C, Matlab/Octave and Python.

Changes:

-Fixed bugs and doc typos


Logo hca 0.61

by wbuntine - September 10, 2014, 03:33:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5802 views, 1124 downloads, 4 subscriptions

About: Multi-core non-parametric and bursty topic models (HDP-LDA, DCMLDA, and other variants of LDA) implemented in C using efficient Gibbs sampling, with hyperparameter sampling and other flexible controls.

Changes:

Corrections to diagnostics and topic report. Correction to estimating alpha. Now estimating beta sometimes (when estimating phi).


Logo Somoclu 1.4

by peterwittek - September 5, 2014, 13:01:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5201 views, 987 downloads, 2 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.

Changes:
  • Better Windows support.
  • Completed CUDA support for Python and R interfaces.
  • Faster compilation by removing unnecessary flags for nvcc
  • Support for CUDA 6.5.
  • Bug fixes: R version no longer needs separate code.

Logo JMLR Darwin 1.8

by sgould - September 3, 2014, 08:42:53 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 30851 views, 6463 downloads, 4 subscriptions

About: A platform-independent C++ framework for machine learning, graphical models, and computer vision research and development.

Changes:

Version 1.8:

  • Added Superpixel Graph Label Transfer (nnGraph) Project project
  • Added Python scripts for automating some projects
  • Added ability to pre-process features on-the-fly with one drwnFeatureTransform when applying or learning another drwnFeatureTransform
  • Fixed race condition in Windows threading (thanks to Edison Guo)
  • Switched Windows and Linux to build against OpenCV 2.4.9
  • Changed drwnMAPInference::inference to return upper and lower energy bounds
  • Added pruneRounds function to drwnBoostedClassifier
  • Added drwnSLICSuperpixels function
  • Added drwnIndexQueue class
  • mexLearnClassifier and mexAnalyseClassifier now support integer label types
  • Bug fix in mexSaveSuperpixels to support single channel

Showing Items 1-20 of 231 on page 1 of 12: 1 2 3 4 5 6 Next Last