Adding support in SparseReader for automatically guessing the number of features in a LibSVM's sparse format file.
Also adding an option for automatically inserting an intercept (bias) term at the beginning of samples being read.
Adding more tracing/debugging information to the TrustRegionNewtonMethod optimizer.
Adding static versions of the transform methods for Linear and Quadratic kernels.
Updating the Polynomial kernel to use those versions when possible.
Marking the TaylorGaussian kernel as serializable.
Fixing the framework random generator seed so it is properly reset when a new seed is given (at least for the current thread).
Adding an intercept property for Generalized Linear Models, some minor additions.
Adding methods to SupportVectorMachine and KernelSupportVectorMachine to convert
to and from arrays containing linear weight coefficients and other linear models.
Updating SVM learning algorithms argument checker to check for NaNs and Infinities.
Adding a base class for support vector machine learning algorithms, and updating SequentialMinimalOptimization
to inherit from this same class. Also fixing an issue in SMO when using separate weights from different classes.
Renaming both CoordinateDescentLinearLearning and NewtonMethodPrimalLearning;
Updating those classes to use the new base class for SVM learning algorithms.
Adding new learning algorithms for creating probabilistic vector machines;
Renaming ProbabilisticOutputLearning to ProbabilisticOutputCalibration.
Adding a new class to load and save models using LibSVM's model definition format.
Updating Accord.Tests.IO folder structure.
Updating unit tests.
Adding a new sample application mimicking most of liblinear's train.exe executable.