Cart (Loading....) | Create Account
Close category search window

Opening the Black Box of Feature Extraction: Incorporating Visualization into High-Dimensional Data Mining Processes

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jianting Zhang ; LTER Network Office, Univ. of New Mexico, Albuquerque, NM ; Gruenwald, L.

Feature extraction techniques have been used to handle high-dimensional data and experimental studies often show improved classification accuracies. Unfortunately very few studies provide concrete evidences on the effectiveness of these feature extraction techniques and they largely remain to be black boxes. In this study, we design and implement a visualization prototype system that allows users to look into the classification processes, explore the links among the original and extracted features in different classifiers, examine why and how an instance is correctly or incorrectly classified. We demonstrate the prototype's capabilities by combining a feature extraction method based on hierarchical feature space clustering with J48 decision tree classifiers and perform experiments on a real hyperspectral remote sensing image dataset.

Published in:

Data Mining, 2006. ICDM '06. Sixth International Conference on

Date of Conference:

18-22 Dec. 2006

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.