New bandwidth selection criterion for Kernel PCA: Approach to dimensionality reduction and classification problems

Published 2014 View Full Article

  1. Home
  2. Publications
  3. Publication Search
  4. Publication Details
Title
New bandwidth selection criterion for Kernel PCA: Approach to dimensionality reduction and classification problems
Authors
Keywords
Feature Selection, Lasso, Little Square Support Vector Machine, Radial Basis Function Kernel, Breast Cancer Data
Journal
BMC BIOINFORMATICS
Volume 15, Issue 1, Pages 137
Publisher
Springer Nature
Online
2014-05-10
DOI
10.1186/1471-2105-15-137
References
View 2 related references

Ask authors/readers for more resources

Protocol

Community support

Reagent

Community support

Reprint

Contact the author

Discover Peeref hubs

Discuss science. Find collaborators. Network.

Join a conversation

Ask a Question. Answer a Question.

Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.

Get Started
Webinars Posters Questions Hubs Funding Journals Articles Connect Collections Reviewers About Us FAQs Mobile App Privacy Policy Terms of Use
© Peeref 2019-2024. All rights reserved.