On merging gradient estimation with mean-tracking techniques for cluster identification THE CURSE OF DIMENSIONALITY
UNSPECIFIED (1997) On merging gradient estimation with mean-tracking techniques for cluster identification THE CURSE OF DIMENSIONALITY. In: 2nd IEEE European Workshop on Computer-Intensive Methods in Control and Signal Processing - Can We Beat the Curse of Dimensionality, AUG 28-30, 1996, PRAGUE, CZECH REPUBLIC.Full text not available from this repository.
This paper discusses how numerical gradient estimation methods may be used in order to reduce the computational demands on a class of multidimensional clustering algorithms. The study is motivated by the recognition that several current point-density based cluster identification algorithms could benefit from a reduction of computational demand if approximate a-priori estimates of the cluster centres present in a given data set could be supplied as starting conditions for these algorithms. In this particular presentation, the algorithm shown to benefit from the technique is the Mean-Tracking (M-T) cluster algorithm, but the results obtained from the gradient estimation approach may also be applied to other clustering algorithms and their related disciplines.
|Item Type:||Conference Item (UNSPECIFIED)|
|Subjects:||Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QA Mathematics
|Journal or Publication Title:||COMPUTER-INTENSIVE METHODS IN CONTROL AND SIGNAL PROCESSING|
|Editor:||Warwick, K and Karny, M|
|Number of Pages:||10|
|Page Range:||pp. 63-72|
|Title of Event:||2nd IEEE European Workshop on Computer-Intensive Methods in Control and Signal Processing - Can We Beat the Curse of Dimensionality|
|Location of Event:||PRAGUE, CZECH REPUBLIC|
|Date(s) of Event:||AUG 28-30, 1996|
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