The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono.

Features

  • Support Vector Machines (multi-class, mult-label, directed acyclic graphs, ... )
  • Conditional Random Fields and Hidden Conditional Random Fields
  • Continuous and Discrete Hidden Markov Models
  • Standard and Multinomial Logistic Regression
  • Second order Neural Network learning algorithms
  • Statistical Analysis (PCA, LDA, KPCA, KDA, PLS, NMF, ... )
  • Hypothesis Testing (Z, F, T, Wald, Bhapkar, Kappa, Kolmogorov, ... )
  • Decision Trees (including automatic code generation)
  • Discrete and Continuous Naive Bayes Classifiers
  • Gaussian Mixture Models
  • Haar-feature image recognition
  • Camshift object tracking
  • Deep learning

Project Samples

Project Activity

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License

GNU Library or Lesser General Public License version 2.0 (LGPLv2)

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Additional Project Details

Operating Systems

Linux, Windows

Intended Audience

Science/Research, Developers, Engineering

User Interface

.NET/Mono, Win32 (MS Windows)

Programming Language

C#, Visual Basic .NET

Related Categories

C# Frameworks, C# Mathematics Software, C# Machine Learning Software, C# Neural Network Libraries, C# Computer Vision Libraries, Visual Basic .NET Frameworks, Visual Basic .NET Mathematics Software, Visual Basic .NET Machine Learning Software, Visual Basic .NET Neural Network Libraries, Visual Basic .NET Computer Vision Libraries

Registered

2012-04-08