Project details for Accord.NET Framework

Screenshot Accord.NET Framework 2.1.5

by cesarsouza - February 21, 2011, 14:49:49 CET [ Project Homepage BibTeX Download ]

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Accord.NET Framework is a C# framework which extends the excellent AForge.NET Framework with new tools and libraries.

The framework is comprised by libraries and sample applications demonstrating their features. Some of the libraries include:

  • Accord.Math - General math and matrix library with numerical decompositions and related linear algebra methods, such as Nonnegative Matrix Factorization, generalized Eigenvalue and others;
  • Accord.Statistics - library with statistical analysis and related tools, such as (Kernel) component and discriminant analysis, partial least squares and hidden Markov models;
  • Accord.Imaging - extension to the AForge.NET Imaging library with new filters and routines;
  • Accord.Neuro - extension to the AForge.NET Neuro library with new algorithms such as Levenberg-Marquardt with Bayesian regularization and Nguyen-Widrow weight initialization;
  • Accord.MachineLearning - extension to AForge's machine learning library with SVMs, K-Means and GMM clustering and related techniques;
  • Accord.Vision - extension to the AForge.NET Vision library with realtime object detectors and trackers such as Viola-Jones and Camshift;
  • Accord.Audio - experimental library with filters and audio processing routines.

For a complete listing of framework features, please see the feature list at

Changes to previous version:

The various works on this release have introduced some breaking interface changes, mainly in the Audio and Statistics namespaces.

  • Adding support for Independent Component Analysis;
  • Adding observation prediction in hidden Markov models;
  • Major reorganization of the hidden Markov models namespace;
  • Major architectural changes on the Accord.Audio namespace;
  • Adding a new algorithm for LDLt Cholesky matrix decomposition;
  • Adding Sparse versions of Gaussian, Polynomial, Laplacian, Sigmoid and Cauchy kernels.

And several other bugfixes and enhancements. For a complete list of changes, please see the full release notes at

BibTeX Entry: Download
Supported Operating Systems: Linux, Windows
Data Formats: Agnostic
Tags: Svm, Kernel Methods, Algorithms, Classifiers, Statistics, Clustering Algorithm, Probability Estimation, Discriminant Analysis, Wavelet Transform, Principal Component Analysis, Algebra, Fourier Transfo
Archive: download here


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