Visual Exploration of Feature-Class Matrices for Classification Problems

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Date
2012
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Volume Title
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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.
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@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
} }
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