MLC++: A Machine Learning Library in C++

Ron Kohavi   George John   Richard Long   David Manley   Karl Pfleger
		     Computer Science Department
			 Stanford University
			  Stanford, CA 94305
			 mlc@CS.Stanford.EDU

We present MLC++, a library of C++ classes and tools for supervised
Machine Learning.  While MLC++ provides general learning algorithms
that can be used by end users, the main objective is to provide
researchers and experts with a wide variety of tools that can
accelerate algorithm development, 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 algorithms and decompose them for a unified
view that is simple, coherent, and extensible.  In this paper we
discuss the problems MLC++ aims to solve, the design of MLC++, and the
current functionality.

Citation:
Ron Kohavi, George John, Richard Long, David Manley, and Karl Pfleger.
MLC++: a machine learning library in C++. In _Sixth National
Conference on Tools with Artificial Intelligence_, pages
740--743. IEEE Press, 1994.