Using topology preservation measures for high-dimensional data analysis in a reduced feature space

• Authors: Szymon Łukasik , Piotr Kulczycki
• Languages of publication: PL

Abstracts

PL

This paper deals with high-dimensional data analysis accomplished through supplementing standard feature extraction procedures with topology preservation measures. This approach is based on an observation that not all elements of an initial dataset are equally preserved in its low-dimensional embedding space representation. The contribution first overviews existing topology preservation measures, then their inclusion in the classical methods of exploratory data analysis is discussed. Finally, some illustrative examples of presented approach in the tasks of cluster analysis and classification are given.

Keywords

PL

multidimensional datasets, dimensionality reduction, topology preservation, cluster analysis, classification

• Publisher: [unknown2]
• Journal: Czasopismo Techniczne
• Year: -

Dates

online

2015-04-29

Contributors

author

Szymon Łukasik

author

Piotr Kulczycki