Causal Discovery Packages

• 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.
• 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.
• Software Packages for Graphical Models: A list maintained by Kevin Murphy of links to software for graphical models/Bayes networks.

Machine Learning Packages

• 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.
• Kernel methods: The kernel machines website provides a list of software for kernel methods, including SVMs. The GKM toolbox provides tools for building generalized kernel machines.
• Software Packages for Machine Learning: A list of machine learning software maintained by David Aha. Commercial packages are found on the KDnuggets website.