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Logo WEKA 3.7.12

by mhall - December 17, 2014, 03:04:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 41531 views, 6136 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 ] 16919 views, 3434 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


Logo Armadillo library 4.550

by cu24gjf - December 5, 2014, 03:24:54 CET [ Project Homepage BibTeX Download ] 47933 views, 10302 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 ] 296 views, 45 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 ] 635 views, 108 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 WolfeSVM 0.0

by utmath - November 19, 2014, 10:46:11 CET [ Project Homepage BibTeX Download ] 356 views, 76 downloads, 2 subscriptions

About: This is a library for solving nu-SVM by using Wolfe's minimum norm point algorithm. You can solve binary classification problem.

Changes:

Initial Announcement on mloss.org.


Logo libcmaes 0.9.3

by beniz - November 17, 2014, 14:04:10 CET [ Project Homepage BibTeX Download ] 2817 views, 589 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 JMLR dlib ml 18.11

by davis685 - November 13, 2014, 23:42:18 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 87580 views, 15170 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 contains mostly minor bug fixes and usability improvements, with the notable exception of new routines for extracting local-binary-pattern features from images and improved tools for learning distance metrics.


Logo Hub Miner 1.0

by nenadtomasev - November 12, 2014, 19:41:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 457 views, 79 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


Logo semi supervised learning for rgb d object recognition 1.0

by openpr_nlpr - November 4, 2014, 03:24:56 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 527 views, 82 downloads, 1 subscription

About: This provide a semi-supervised learning method based co-training for RGB-D object recognition. Besides, we evaluate four state-of-the-art feature learing method under the semi-supervised learning framework.

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 ] 388 views, 93 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.


Logo pySPACE 1.2

by krell84 - October 29, 2014, 15:36:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2320 views, 490 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 BACOM2 1.0

by fydennis - October 24, 2014, 15:25:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 492 views, 84 downloads, 2 subscriptions

About: revised version of BACOM

Changes:

Initial Announcement on mloss.org.


Logo BayesOpt, a Bayesian Optimization toolbox 0.7.2

by rmcantin - October 10, 2014, 19:12:59 CET [ Project Homepage BibTeX Download ] 9816 views, 2010 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 AugmentedSVM 1.0.0

by ashukla - October 2, 2014, 11:24:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 798 views, 156 downloads, 2 subscriptions

About: A MATLAB toolkit for performing generalized regression with equality/inequality constraints on the function value/gradient.

Changes:

Initial Announcement on mloss.org.


Logo JMLR Darwin 1.8

by sgould - September 3, 2014, 08:42:53 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 30727 views, 6439 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

Logo XGBoost v0.3.0

by crowwork - September 2, 2014, 02:43:31 CET [ Project Homepage BibTeX Download ] 3293 views, 630 downloads, 2 subscriptions

About: xgboost: eXtreme Gradient Boosting It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithm. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm or sklearn.GBM . It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that user are also allowed to define there own objectives easily.

Changes:

New features: - R support that is now on CRAN

  • Faster tree construction module

  • Support for boosting from initial predictions

  • Linear booster is now parallelized, using parallel coordinated descent.


Logo Salad 0.5.0

by chwress - August 22, 2014, 17:54:56 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4672 views, 843 downloads, 1 subscription

About: A Content Anomaly Detector based on n-Grams

Changes:

Lots and lots of cool new features and bugfixes ;)

  • Refinements to the user interface: This includes a progress indicator, colors, etc.
  • Determine the expected error (salad-inspect)
  • Enable the user to echo the used parametrization: salad [train|predict|inspect] --echo-params
  • Allow to set the input batch size as program argument: salad [train|predict|inspect] --batch-size
  • libsalad: The library allows to access salad's basic functions
  • Installers and precompiled binaries: Windows installer, Debian (ppa:chwress/salad) & RPM packages as well a generic linux installers.
  • Various minor bug fixes
  • Support for "length at end" zip files
  • Improve salad's usage in a 2-class setting: salad [train|predict|inspect] --input-filter

Logo QSMM 1.16

by olegvol - July 29, 2014, 19:37:31 CET [ Project Homepage BibTeX Download ] 656 views, 185 downloads, 3 subscriptions

About: The implementation of adaptive probabilistic mappings.

Changes:

Initial Announcement on mloss.org.


Logo JMLR Waffles 2014-07-05

by mgashler - July 20, 2014, 04:53:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 25269 views, 7387 downloads, 2 subscriptions

About: Script-friendly command-line tools for machine learning and data mining tasks. (The command-line tools wrap functionality from a public domain C++ class library.)

Changes:

Added support for CUDA GPU-parallelized neural network layers, and several other new features. Full list of changes at http://waffles.sourceforge.net/docs/changelog.html


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