Preprint: Error-correcting output codes
Tom Dietterich
tgd at turing.CS.ORST.EDU
Thu Apr 18 00:14:11 EDT 1991
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The following preprint is available for FTP access from the Ohio State
Neuroprose archive:
Error-Correcting Output Codes:
A General Method for Improving
Multiclass Inductive Learning Programs
Thomas G. Dietterich and Ghulum Bakiri
Department of Computer Science
Oregon State University
Corvallis, OR 97331-3202
Multiclass learning problems involve finding a definition for an
unknown function f(x) whose range is a discrete set containing k>2
values (i.e., k ``classes''). The definition is acquired by studying
large collections of training examples of the form <x_i, f(x_i)>.
Existing approaches to this problem include (a) direct application of
multiclass algorithms such as the decision-tree algorithms ID3 and
CART, (b) application of binary concept learning algorithms to learn
individual binary functions for each of the k classes, and (c)
application of binary concept learning algorithms with distributed
output codes such as those employed by Sejnowski and Rosenberg in the
NETtalk system. This paper compares these three approaches to a new
technique in which BCH error-correcting codes are employed as a
distributed output representation. We show that these
error-correcting output representations improve the performance of ID3
on the NETtalk task and of backpropagation on an isolated-letter
speech-recognition task. These results demonstrate that
error-correcting output codes provide a general-purpose method for
improving the performance of inductive learning programs on multiclass
problems.
This paper will appear in AAAI-91.
To retrieve:
unix> ftp cheops.cis.ohio-state.edu (or 128.146.8.62)
Name: anonymous
Password: your-name at your-address
ftp> cd pub/neuroprose
ftp> binary
ftp> get dietterich.error-correcting.ps.Z
ftp> bye
unix> uncompress dietterich.error-correcting.ps.Z
unix> lpr -P{postscript printer} dietterich.error-correcting.ps
Thank-you to Jordan Pollack for providing the ftp services.
--Tom
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