English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
 Local TagsRelease HistoryDetailsSummary
  Classification on proximity data with LP-machines

Graepel, T., Herbrich, R., Schölkopf, B., Smola, A., Bartlett, P., Müller, K., et al. (1999). Classification on proximity data with LP-machines. In Ninth International Conference on Artificial Neural Networks ICANN 99 (pp. 304-309). London, UK: Institute of Electrical Engineers.

Item is

 

show all hide all

Basic

show hide
Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-E753-2 Version Permalink: https://hdl.handle.net/21.11116/0000-0005-C157-F
Genre: Conference Paper

Files

show Files

Locators

show
hide
Locator:
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=819738 (Publisher version)
Description:
-
OA-Status:

Creators

show
hide
 Creators:
Graepel, T, Author
Herbrich, R, Author
Schölkopf, B1, Author           
Smola, AJ, Author           
Bartlett, P, Author
Müller, K, Author
Obermayer, K, Author
Williamson, RC, Author
Affiliations:
1External Organizations, ou_persistent22              

Content

show
hide
Free keywords: -
 Abstract: We provide a new linear program to deal with classification of data in the case of data given in terms of pairwise proximities. This allows to avoid the problems inherent in using feature spaces with indefinite metric in support vector machines, since the notion of a margin is purely needed in input space where the classification actually occurs. Moreover in our approach we can enforce sparsity in the proximity representation by sacrificing training error. This turns out to be favorable for proximity data. Similar to /spl nu/-SV methods, the only parameter needed in the algorithm is the (asymptotical) number of data points being classified with a margin. Finally, the algorithm is successfully compared with /spl nu/-SV learning in proximity space and K-nearest-neighbors on real world data from neuroscience and molecular biology.

Details

show
hide
Language(s):
 Dates: 1999-09
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 811
DOI: 10.1049/cp:19991126
 Degree: -

Event

show
hide
Title: Ninth International Conference on Artificial Neural Networks (ICANN 1999)
Place of Event: Edinburgh, UK
Start-/End Date: 1999-09-07 - 1999-09-10

Legal Case

show

Project information

show

Source 1

show
hide
Title: Ninth International Conference on Artificial Neural Networks ICANN 99
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: London, UK : Institute of Electrical Engineers
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 304 - 309 Identifier: ISBN: 0-85296-721-7

Source 2

show
hide
Title: Conference Publication of the Institution of Electrical Engineers
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 470 Sequence Number: - Start / End Page: - Identifier: -