Dependence maps, a dimensionality reduction with dependence distance for high-dimensional data
- Authors
- Lee, Kichun; Gray, Alexander; Kim, Heeyoung
- Issue Date
- May-2013
- Publisher
- SPRINGER
- Keywords
- Dependence maps; Dimensionality reduction; Dependence; Markov chain
- Citation
- DATA MINING AND KNOWLEDGE DISCOVERY, v.26, no.3, pp.512 - 532
- Indexed
- SCIE
SCOPUS
- Journal Title
- DATA MINING AND KNOWLEDGE DISCOVERY
- Volume
- 26
- Number
- 3
- Start Page
- 512
- End Page
- 532
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/162843
- DOI
- 10.1007/s10618-012-0267-9
- ISSN
- 1384-5810
- Abstract
- We introduce the dependence distance, a new notion of the intrinsic distance between points, derived as a pointwise extension of statistical dependence measures between variables. We then introduce a dimension reduction procedure for preserving this distance, which we call the dependence map. We explore its theoretical justification, connection to other methods, and empirical behavior on real data sets.
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