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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
Categories
Frameworks, Mathematics, Machine Learning, Neural Network Libraries, Computer Vision Libraries, Deep Learning FrameworksLicense
GNU Library or Lesser General Public License version 2.0 (LGPLv2)nel_h2
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