About: 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 an extensive online documentation helps fill in the details.

For a complete list of changes, please see the full release notes at the release details page at:

https://github.com/accord-net/framework/releases/tag/v3.8.0

About: C++ software for statistical classification, probability estimation and interpolation/non-linear regression using variable bandwidth kernel estimation.

New in Version 0.9.8:

• bug fixes: svm file conversion works properly and is more general

• non-hierarchical multi-borders has 3 options for solving for the conditional probabilities: matrix inversion, voting, and matrix inversion over-ridden by voting, with re-normalization

• multi-borders now works with external binary classifiers

• random numbers resolve a tie when selecting classes based on probabilities

• pair of routines, sort_discrete_vectors and search_discrete_vectors, for classification based on n-d binning (still experimental)

• command options have been changed with many new additions, see QUICKSTART file or run the relevant commands for details

About: Matlab code for learning probabilistic SVM in the presence of uncertain labels.

Added missing dataset function (thanks to Hao Wu)

About: Tools for functional network analysis.

Initial Announcement on mloss.org.