Accord.NET Framework 3.3.0 freeware

... computer vision. It includes several methods for statistical analysis, such as Principal Component Analysis, Linear Discriminant Analysis, Partial Least Squares. ...

Author Cesar Roberto de Souza
Released 2016-09-17
Filesize 483.00 MB
Downloads 1250
OS Windows XP, Windows Vista, Windows Vista x64, Windows 7, Windows 7 x64, Windows 8, Windows 8 x64, Windows 10, Windows 10 x64
Installation Instal And Uninstall
Keywords .NET Framework, C# Framework, AForge.NET Framework, Framework, AForge.NET, .NET
Users' rating
(35 rating)
Accord.NET FrameworkComponents & LibrariesWindows XP, Windows Vista, Windows Vista x64, Windows 7, Windows 7 x64, Windows 8, Windows 8 x64, Windows 10, Windows 10 x64
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Accord.NET Framework freeware - The Latest User Reviews
Accord.NET Framework freeware - The Latest Versions History
3.3.0 Sep 17, 2016 New Release General:
This will be last release that includes an executable installer. If you are still using the installer, please move to NuGet or use the framework compressed archive files.

Imaging:
Creating a new Accord.Imaging.Noncommercial assembly to hold non-commercial imaging methods;
Adding Fast Guided Filter to Accord.Imaging.Noncommercial.

MachineLearning:
Fixing Binary Split's learn method to accept null weights;
Updating Binary Split example to reflect the new API;
Adding constructors to allow tree inducing algorithms to create a tree from scratch;

Statistics:
Fixing multiple issues with statistical analyses classes when they are used using the new classification/regression APIs;
Statistical measures (Measures.cs) have been moved to the Accord.Math assembly,
but have been kept under the Accord.Statistics namespace;
Correcting L2-regularization in Logistic Regression.
2.12.0 Aug 8, 2014 New Release
2.9.0 Jul 16, 2013 New Release General:
· Working on more source code examples for the documentation.

Accord.Math:
· Adding Levenshtein distance for strings.

Accord.Imaging:
· Updating BagOfVisualWords to be fully serializable.

Accord.MachineLearning:
· 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.

Accord.Statistics:
· 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;

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