Visual Exploration of Feature-Class Matrices for Classification Problems
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Date
2012
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
When a classification algorithm does not work on a data set, it is a non-trivial problem to figure out what went wrong on a technical level. It is even more challenging to communicate findings to domain experts who can interpret the data set but do not understand the algorithms. We propose a method for the interactive visual exploration of the feature-class matrix used to represent data sets for classification purposes. This method combines a novel matrix reordering algorithm revealing patterns of interest with an interactive visualization application. It facilitates the investigation of feature-class matrices and the identification of reasons for failure or success of a classifier on the feature level. We discuss results obtained by applying the method to the Reuters text collection.
Description
@inproceedings{:10.2312/PE/EuroVAST/EuroVA12/037-041,
booktitle = {EuroVA 2012: International Workshop on Visual Analytics},
editor = {Kresimir Matkovic and Giuseppe Santucci},
title = {{Visual Exploration of Feature-Class Matrices for Classification Problems}},
author = {Kienreich, Wolfgang and Seifert, Christin},
year = {2012},
publisher = {The Eurographics Association},
ISBN = {978-3-905673-89-0},
DOI = {/10.2312/PE/EuroVAST/EuroVA12/037-041}
}