Search Results for "learning vector quantization"

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 extensive documentation and a wiki help fill in the details. The Accord.NET project provides...

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.

GPU Machine Learning Library. This library aims to provide machine learning researchers and practitioners with a high performance library by taking advantage of the GPU enormous computational power. The library is developed in C++ and CUDA.

SVM# is a svm(support vector machine) classification implemented in C#. The project contains both train and predict modules.