Accord.NET Framework is useful tool that intends to enhance the features of the 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.Statistics - library with statistical analysis and other tools;
Accord.Imaging - extension to the AForge.NET Imaging library with new filters and routines;
Accord.Neuro - extension to the AForge.NET Neuro library with other learning algorithms;
Accord.MachineLearning - extension to AForge's machine learning library with Support Vector Machines;
Accord.Vision - extension to the AForge.NET Vision library with realtime object detectors and trackers;
Accord.Audio - experimental library with filters and audio processing routines.
Note: In order to use Accord.NET, you must have AForge.NET already installed.
- Working on more source code examples for the documentation.
- Adding Levenshtein distance for strings.
- Updating BagOfVisualWords to be fully serializable.
- Adding K-dimensional trees (K-d trees);
- Adding Mean-Shift clustering algorithm;
- Adding support for weights in Gaussian Mixture Models;
- Correcting the name of the K-Nearest Neighbors algorithm;
- Improving K-Nearest Neighbors for double using a K-d tree;
- Changing K-Nearest Neighbors generic argument to represent the
- instance type rather than the type of the array of instances.
- Adding interfaces for density estimation kernels;
- Adding Gaussian, Epanechnikov, Uniform density kernels;
- Adding Bartlett's and Levene's tests for variances;
- Adding hypothesis tests for comparing ROC curves;
- Adding support for scatterplot generation directly from ROC curves;
- Adding running Markov models and running Markov classifier filters;
- Adding stoch...