- FACTORIE is a toolkit for deployable probabilistic modeling, implemented as a software library in Scala.
It provides its users with a succinct language for creating relational
factor graphs, estimating parameters and performing inference. It
is flexible, supporting multiple modeling and inference paradigms. Its
original emphasis was on conditional random fields, undirected
graphical models, MCMC inference, online training, and discriminative
parameter estimation. However, it now also supports directed generative
models (such as latent Dirichlet allocation), and has preliminary
support for variational inference, including belief propagation and
mean-field methods. It is also scalable, with demonstrated
success on problems with many millions of variables and factors, and on
models that have changing structure, such as case factor diagrams. It
has also been plugged into a database back-end, representing a new
approach to probabilistic databases capable of handling billions of
- MALLET is a
library of Java code for machine learning applied to text. It provides
facilities not only for document classification, but also information
extraction, part-of-speech tagging, noun phrase segmentation, and much
more. The development of the library is quite mature, however it does
not yet have as polished front-ends or documentation as rainbow.
- Libbow is a library of C code for document classification, clustering and retrieval. Also provided with the library is rainbow, its popular
front-end for document classification, and archer, a speedy disk-based
document retrieval engine with an AltaVista-like query interface, with
the ability to handle several gigabytes of text.
- Cora HMM is the C implementation of HMMs used for information extraction in Cora. It was written by Kristie Seymore.
- RLKIT a software library that makes it
easy to test various reinforcement learning algorithms in different
environments with different sensory-motor systems. It's implemented
in Objective-C and GNU Guile (Scheme).