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Logo python weka wrapper 0.2.0

by fracpete - December 22, 2014, 09:21:53 CET [ Project Homepage BibTeX Download ] 6872 views, 1440 downloads, 3 subscriptions

About: A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls.

Changes:

NB: This release is not backwards compatible!

  • requires "JavaBridge" 1.0.9 at least
  • moved from Java-like get/set ("getIndex()" and "setIndex(int)") to nicer Python properties
  • using Python properties (also only read-only ones) wherevere possible
  • added "weka.core.version" for accessing the Weka version currently in use
  • added "jwrapper" and "jclasswrapper" methods to "JavaObject" class (the mother of all objects in python-weka-wrapper) to allow generic access to an object's methods: http://pythonhosted.org//javabridge/highlevel.html#wrapping-java-objects-using-reflection
  • added convenience methods "class_is_last()" and "class_is_first()" to "weka.core.Instances" class
  • added convenience methods "delete_last_attribute()" and "delete_first_attribute()" to "weka.core.Instances" class

Logo JMLR dlib ml 18.12

by davis685 - December 20, 2014, 22:38:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 87911 views, 15209 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 ] 41696 views, 6162 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 JMLR MLPACK 1.0.11

by rcurtin - December 11, 2014, 18:20:35 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 35845 views, 7020 downloads, 6 subscriptions

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

Changes:
  • Proper handling of dimension calculation in PCA.
  • Load parameter vectors properly for LinearRegression models.
  • Linker fixes for AugLagrangian specializations under Visual Studio.
  • Add support for observation weights to LinearRegression.
  • MahalanobisDistance<> now takes root of the distance by default and therefore satisfies the triangle inequality (TakeRoot now defaults to true).
  • Better handling of optional Armadillo HDF5 dependency.
  • Fixes for numerous intermittent test failures.
  • math::RandomSeed() now sets the seed for recent (>= 3.930) Armadillo versions.
  • Handle Newton method convergence better for SparseCoding::OptimizeDictionary() and make maximum iterations a parameter.
  • Known bug: CosineTree construction may fail in some cases on i386 systems (376).

Logo JMLR JKernelMachines 2.5

by dpicard - December 11, 2014, 17:51:42 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14099 views, 3422 downloads, 4 subscriptions

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About: machine learning library in java for easy development of new kernels

Changes:

Version 2.5

  • New active learning algorithms
  • Better threading management
  • New multiclass SVM algorithm based on SDCA
  • Handle class balancing in cross-validation
  • Optional support of EJML switch to version 0.26
  • Various bugfixes and improvements

Logo APCluster 1.4.1

by UBod - December 10, 2014, 12:58:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 18511 views, 3392 downloads, 3 subscriptions

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About: The apcluster package implements Frey's and Dueck's Affinity Propagation clustering in R. The package further provides leveraged affinity propagation, exemplar-based agglomerative clustering, and various tools for visual analysis of clustering results.

Changes:
  • fixes in C++ code of sparse affinity propagation

Logo Accord.NET Framework 2.14.0

by cesarsouza - December 9, 2014, 23:04:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 16995 views, 3452 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 JMLR GPML Gaussian Processes for Machine Learning Toolbox 3.5

by hn - December 8, 2014, 13:54:38 CET [ Project Homepage BibTeX Download ] 20592 views, 4807 downloads, 3 subscriptions

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About: The GPML toolbox is a flexible and generic Octave 3.2.x and Matlab 7.x implementation of inference and prediction in Gaussian Process (GP) models.

Changes:
  • mechanism for specifying hyperparameter priors (together with Roman Garnett and José Vallet)
  • new inference method inf/infGrid allowing efficient inference for data defined on a Cartesian grid (together with Andrew Wilson)
  • new mean/cov functions for preference learning: meanPref/covPref
  • new mean/cov functions for non-vectorial data: meanDiscrete/covDiscrete
  • new piecewise constant nearest neighbor mean function: meanNN
  • new mean functions being predictions from GPs: meanGP and meanGPexact
  • new covariance function for standard additive noise: covEye
  • new covariance function for factor analysis: covSEfact
  • new covariance function with varying length scale : covSEvlen
  • make covScale more general to scaling with a function instead of a scalar
  • bugfix in covGabor* and covSM (due to Andrew Gordon Wilson)
  • bugfix in lik/likBeta.m (suggested by Dali Wei)
  • bugfix in solve_chol.c (due to Todd Small)
  • bugfix in FITC inference mode (due to Joris Mooij) where the wrong mode for post.L was chosen when using infFITC and post.L being a diagonal matrix
  • bugfix in infVB marginal likelihood for likLogistic with nonzero mean function (reported by James Lloyd)
  • removed the combination likErf/infVB as it yields a bad posterior approximation and lacks theoretical justification
  • Matlab and Octave compilation for L-BFGS-B v2.4 and the more recent L-BFGS-B v3.0 (contributed by José Vallet)
  • smaller bugfixes in gp.m (due to Joris Mooij and Ernst Kloppenburg)
  • bugfix in lik/likBeta.m (due to Dali Wei)
  • updated use of logphi in lik/likErf
  • bugfix in util/solve_chol.c where a typing issue occured on OS X (due to Todd Small)
  • bugfix due to Bjørn Sand Jensen noticing that cov_deriv_sq_dist.m was missing in the distribution
  • bugfix in infFITC_EP for ttau->inf (suggested by Ryan Turner)

Logo libAGF 0.9.8

by Petey - December 6, 2014, 02:35:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9290 views, 1852 downloads, 2 subscriptions

About: C++ software for statistical classification, probability estimation and interpolation/non-linear regression using variable bandwidth kernel estimation.

Changes:

New in Version 0.9.8:

  • bug fixes: svm file conversion works properly and is more general

  • non-hierarchical multi-borders has 3 options for solving for the conditional probabilities: matrix inversion, voting, and matrix inversion over-ridden by voting, with re-normalization

  • multi-borders now works with external binary classifiers

  • random numbers resolve a tie when selecting classes based on probabilities

  • pair of routines, sort_discrete_vectors and search_discrete_vectors, for classification based on n-d binning (still experimental)

  • command options have been changed with many new additions, see QUICKSTART file or run the relevant commands for details


Logo The Statistical ToolKit 0.8.4

by joblion - December 5, 2014, 13:21:47 CET [ Project Homepage BibTeX Download ] 678 views, 198 downloads, 2 subscriptions

About: STK++: A Statistical Toolkit Framework in C++

Changes:

Inegrating openmp to the current release. Many enhancement in the clustering project. bug fix


Showing Items 1-10 of 552 on page 1 of 56: 1 2 3 4 5 6 Next Last