English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Logistic Regression for Graph Classification

Shervashidze, N., & Tsuda, K. (2008). Logistic Regression for Graph Classification. In NIPS 2008: Mini Symposia & Workshops (pp. 75).

Item is

Files

show Files

Locators

show
hide
Description:
-
OA-Status:

Creators

show
hide
 Creators:
Shervashidze, N1, 2, Author           
Tsuda, K1, 2, Author           
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

Content

show
hide
Free keywords: -
 Abstract: In this paper we deal with graph classification. We propose a new algorithm for performing sparse logistic regression for graphs, which is comparable in accuracy with other methods of graph classification and produces probabilistic output in addition. Sparsity is required for the reason of interpretability, which is often necessary in domains such as bioinformatics or chemoinformatics.

Details

show
hide
Language(s):
 Dates: 2008-12
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 5685
 Degree: -

Event

show
hide
Title: NIPS 2008 Workshop: Structured Input - Structured Output (NIPS SISO 2008)
Place of Event: Whistler, BC, Canada
Start-/End Date: 2008-12-12

Legal Case

show

Project information

show

Source 1

show
hide
Title: NIPS 2008: Mini Symposia & Workshops
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 75 Identifier: -