TY - JOUR
TI - Using topology preservation measures for high-dimensional data analysis in a reduced feature space
AU - Łukasik, Szymon
AU - Kulczycki, Piotr
TI - Using topology preservation measures for high-dimensional data analysis in a reduced feature space
AB - 
	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.
VL - 2012
IS - Automatyka Zeszyt 1-AC (25) 2012
PY - 2012
SN - 0011-4561
C1 - 2353-737X
SP - 1
EP - 1
DO - 10.4467/2353737XCT.14.001.1778
UR - https://ejournals.eu/czasopismo/czasopismo-techniczne/artykul/using-topology-preservation-measures-for-high-dimensional-data-analysis-in-a-reduced-feature-space
KW - multidimensional datasets
KW - dimensionality reduction
KW - topology preservation
KW - cluster analysis
KW - classification