Causal explorer: A causal probabilistic network learning toolkit for Matlab (R). This package supports "local" causal discovery algorithms, efficient to discover the causal structure around a target variable, even for a large number of variables.
Causality@Tuebingen: Algorithms for causal discovery, including cause-effect pair algorithms and the HSIC test.
TETRAD: A standalone program for creating, simulating data from, estimating, testing, predicting with, and searching for causal/statistical models.
Bayes Net Toolbox: A Matlab (R) toolbox supporting many types of graphical models and learning algorithms.
GLOP: A Matlab (R) package providing models included in the Virtual Lab of the Cusality Workbench. Partially based on the Bayes Net Toolbox.
Challenge Learning Object Package(CLOP): An object-oriented Matlab(R) library of machine learning algorithms having performed well in past challenges, including ridge regression, SVMs, boosting, and random forests. It provides an interface to Weka and R.
Weka: A standalone data mining environment written in Java.
R: A software environment for statistical computing including many machine learning algorithms.
The kernel machines website provides a list of software for kernel methods, including SVMs. The GKM toolbox provides tools for building generalized kernel machines.