MLC++ is a library of C++ classes for supervised machine learning. The MLC++ utilities were created using the library.

MLC++ (up to version 1.3.X) was developed at Stanford University and was public domain; that version is still distributed as such by SGI. SGI MLC++ (V2.0 and higher) includes improvements to MLC++. These improvements are research domain only and are available in both source and object code formats through this web site.

SGI MLC++ is used in SGI's MineSet product as the main engine for the server data mining.

MLC++ provides general machine learning algorithms that can be used by end users, analysts, professionals, and researchers. The main objective is to provide users with a wide variety of tools that can help mine data, accelerate development of new mining algorithms, increase software reliability, provide comparison tools, and display information visually.

More than just a collection of existing algorithms, MLC++ is an attempt to extract commonalities of machine learning algorithms and decompose them for a unified view that is simple, coherent, and extensible.

Datasets from UCI that were converted to MLC++ format are available here.