New paper in neuroprose

[dhw@santafe.edu]

                *** DO NOT FORWARD TO ANY OTHER LISTS ***


The following file has been placed in neuroprose. Part of it consists
of a tutorial review, and part of it consists of novel material
concerning extensions of stacked generalization.



	COMBINING GENERALIZERS USING PARTITIONS OF THE LEARNING SET


			by David H. Wolpert 



Abstract: For any real-world generalization problem, there are always
many generalizers which could be applied to the problem. This paper
discusses some algorithmic techniques for dealing with this
multiplicity of possible generalizers. All of these techniques rely on
partitioning the provided learning set in two, many different times.
The first technique discussed is cross-validation, which is a
winner-takes-all strategy (based on the behavior of the generalizers
on the partitions of the learning set, it picks one single generalizer
from amongst the set of candidate generalizers, and tells you to use
that generalizer). The second technique discussed, the one this paper
concentrates on, is an extension of cross-validation called stacked
generalization. As opposed to cross-validation's winner-takes-all
strategy, stacked generalization uses the partitions of the learning
set to combine the generalizers, in a non-linear manner, via another
generalizer (hence the term `stacked generalization'). After
presenting a cursory review of stacked generalization, this paper
discusses some possible extensions of stacked generalization.




To retrieve the file:

unix> ftp cheops.cis.ohio-state.edu
Connected to cheops.cis.ohio-state.edu.
220 cheops.cis.ohio-state.edu FTP server ready.
Name: anonymous
331 Guest login ok, send ident as password.
Password:neuron
230 Guest login ok, access restrictions apply.
ftp> binary
200 Type set to I.
ftp> cd pub/neuroprose
250 CWD command successful.
ftp> get wolpert.lecture92.ps.Z
200 PORT command successful.
150 Opening BINARY mode data connection for rosenblatt.reborn.ps.Z
226 Transfer complete.
100000 bytes sent in 3.14159 seconds
ftp> quit
221 Goodbye.
unix> uncompress wolpert.lecture92.ps.Z
unix lpr wolpert.lecture92.ps (or however you print out postscript)



Many thanks to Jordan Pollack for maintaining this archive.