Taxonomy Inference Using Kernel Dependence Measures

Blaschko, MB; Gretton, A

Local TagsRelease HistoryDetailsSummary

Taxonomy Inference Using Kernel Dependence Measures

Blaschko, M., & Gretton, A.(2008). Taxonomy Inference Using Kernel Dependence Measures (181). Tübingen, Germany: Max Planck Institute for Biological Cybernetics.

Item is Released

show all hide all

Basic

show hide

Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-C673-4 Version Permalink: https://hdl.handle.net/21.11116/0000-0002-8702-3

Genre: Report

Files

show Files

hide Files

:

MPIK-TR-181.pdf (Publisher version), 722KB

View Save

File Permalink:
https://hdl.handle.net/21.11116/0000-0002-8703-2

Name:
MPIK-TR-181.pdf

Description:
-

OA-Status:

Visibility:
Public

MIME-Type / Checksum:
application/pdf / [MD5]

Technical Metadata:

View

Copyright Date:
-

Copyright Info:
-

License:
-

Locators

show

Creators

show

hide

Creators:
Blaschko, MB^{1, 2}, Author
Gretton, A^{1, 2}, Author

Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794

Content

show

hide

Free keywords: -

Abstract: We introduce a family of unsupervised algorithms, numerical taxonomy clustering, to simultaneously
cluster data, and to learn a taxonomy that encodes the relationship between the clusters. The algorithms
work by maximizing the dependence between the taxonomy and the original data. The resulting taxonomy is a
more informative visualization of complex data than simple clustering; in addition, taking into account the relations
between different clusters is shown to substantially improve the quality of the clustering, when compared
with state-of-the-art algorithms in the literature (both spectral clustering and a previous dependence maximization
approach). We demonstrate our algorithm on image and text data.

Details

show

hide

Language(s):

Dates: Date issued: 2008-11

Publication Status: Issued

Pages: 11

Publishing info: Tübingen, Germany : Max Planck Institute for Biological Cybernetics

Table of Contents: -

Rev. Type: -

Identifiers: Report Nr.: 181
BibTex Citekey: 5618

Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show

hide

Title: Technical Report of the Max Planck Institute for Biological Cybernetics

Source Genre: Series

Creator(s):

Affiliations:

Publ. Info: -

Pages: - Volume / Issue: 181 Sequence Number: - Start / End Page: - Identifier: -