MLC++: a machine learning library in C++

Author

Kohavi, Ron ; John, George ; Long, Richard ; Manley, David ; Pfleger, Karl

Author_Institution

Dept. of Comput. Sci., Stanford Univ., CA, USA

fYear

1994

fDate

6-9 Nov 1994

Firstpage

740

Lastpage

743

Abstract

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 can 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

Keywords

C language; learning (artificial intelligence); software reliability; C++; MLC++; algorithm development; comparison tools; machine learning library; software reliability; Acceleration; Computer science; Data mining; Displays; Libraries; Machine learning; Machine learning algorithms; Programming profession; Testing; Tree graphs;

fLanguage

English

Publisher

ieee

Conference_Titel

Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on

Conference_Location

New Orleans, LA

Print_ISBN

0-8186-6785-0

Type

conf

DOI

10.1109/TAI.1994.346412

Filename

346412