Bibliographic Details
| Title: |
Dependence maps, a dimensionality reduction with dependence distance for high-dimensional data. |
| Authors: |
Lee, Kichun1 skylee@hanyang.ac.kr, Gray, Alexander2 agray@cc.gatech.edu, Kim, Heeyoung3 hykim@gatech.edu |
| Source: |
Data Mining & Knowledge Discovery. May2013, Vol. 26 Issue 3, p512-532. 21p. 5 Diagrams, 6 Graphs. |
| Subjects: |
Statistical maps, Electronic data processing, Dimension reduction (Statistics), Dependence (Statistics), Markov processes, Data analysis |
| 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. [ABSTRACT FROM AUTHOR] |
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| Database: |
Engineering Source |
