Visual Exploration of Feature-Class Matrices for Classification Problems
| dc.contributor.author | Kienreich, Wolfgang | en_US |
| dc.contributor.author | Seifert, Christin | en_US |
| dc.contributor.editor | Kresimir Matkovic and Giuseppe Santucci | en_US |
| dc.date.accessioned | 2013-11-08T10:21:28Z | |
| dc.date.available | 2013-11-08T10:21:28Z | |
| dc.date.issued | 2012 | en_US |
| dc.description.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. | en_US |
| dc.description.seriesinformation | EuroVA 2012: International Workshop on Visual Analytics | en_US |
| dc.identifier.isbn | 978-3-905673-89-0 | en_US |
| dc.identifier.uri | https://doi.org/10.2312/PE/EuroVAST/EuroVA12/037-041 | en_US |
| dc.publisher | The Eurographics Association | en_US |
| dc.title | Visual Exploration of Feature-Class Matrices for Classification Problems | en_US |
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