MLC++ : Machine learning library in C++

[Ronny Kohavi]

MLC++ is a machine learning library developed in C++.
MLC++ is public domain and can be used free of charge,
including use of the source code.

MLC++ contains common induction algorithms, such as ID3,
nearest-neighbors, naive-bayes, oneR (Holte), winnow, and decision
tables, all written under a single framework.

MLC++ also contains interfaces to common algorithms, such
as C4.5, PEBLS, IB1-4,  OC1, CN2.

MLC++ contains wrappers to wrap around algorithms.
These include: feature selection, discretization filters,
automatic parameter setting for C4.5, bagging/combinining classifiers,
and more.

Finally, MLC++ contains common accuracy estimation methods, such as
holdout, cross-validation, and bootstrap .632.

Interfaces to existing algorithms are not hard to create and
implementing new algorithms in MLC++ is possible with added benefits
(some procedures work only on induction algorithms implemented in
MLC++ as opposed to interfaced ones).

Object code for MLC++ utilities is provided for Silicon Graphic
machines running Irix 5.3.

To contact us, send e-mail to: mlc at postofc.corp.sgi.com
Visit our web page at: http://www.sgi.com/Technology/mlc/

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   Ronny Kohavi (ronnyk at sgi.com, http://robotics.stanford.edu/~ronnyk)