Numerical Algorithms

• A fast matrix object implemented using the expression templates technique and capable of using BLAS and LAPACK libraries when available.
• Numerous linear algebra and mathematical operations are defined for the matrix object such as the singular value decomposition, transpose, trig functions, etc.
• General purpose unconstrained non-linear optimization algorithms using the conjugate gradient, BFGS, and L-BFGS techniques
• Levenberg-Marquardt for solving non-linear least squares problems
• Box-constrained derivative-free optimization via the BOBYQA algorithm
• An implementation of the Optimized Cutting Plane Algorithm
• Several quadratic program solvers
• A big integer object
• A random number object

Machine Learning Algorithms

• Conventional SMO based Support Vector Machines for classification and regression
• Reduced-rank methods for large-scale classification and regression
• Relevance vector machines for classification and regression
• General purpose multiclass classification tools
• A Multiclass SVM
• A tool for solving the optimization problem associated with structural support vector machines.
• An online kernel RLS regression algorithm
• An online SVM classification algorithm
• An online kernelized centroid estimator/novelty detector
and offline support vector

one-class classification

A kernelized k-means clustering algorithm

Radial Basis Function Networks

Multi layer perceptrons

Bayesian Network Inference Algorithms

• join tree algorithm for exact inference
• gibbs sampler markov chain monte carlo algorithm

That’s a lot of stuff packed in there ;-)