A new Distance Function for Prototype based Clustering Algorithms in High Dimensional Spaces
Winkler, Roland and Klawonn, Frank and Kruse, Rudolf (2011) A new Distance Function for Prototype based Clustering Algorithms in High Dimensional Spaces. CLADAG 2011, 07.-09. Sep 2011, Pavia, Italien.
Full text not available from this repository.
Abstract High dimensional data analysis poses some interesting and counter intuitive problems. One of this problems is, that some clustering algorithms do not work or work only very poorly if the dimensionality is high enough. The reason for this is an effect called distance concentration. In this paper, we show that the effect can be countered for prototype based clustering algorithms by using a clever alteration of the distance function. We show the success of this process by applying (but not restricting) it on FCM. A useful side effect is, that our method can also be used to estimate the number of clusters in a data set.
|Document Type:||Conference or Workshop Item (Speech, Paper)|
|Title:||A new Distance Function for Prototype based Clustering Algorithms in High Dimensional Spaces|
|Keywords:||curse of dimensionality, distance concentration, prototype based clustering, fuzzy c-means|
|Event Title:||CLADAG 2011|
|Event Location:||Pavia, Italien|
|Event Type:||international Conference|
|Event Dates:||07.-09. Sep 2011|
|Organizer:||University of Pavia|
|HGF - Research field:||Aeronautics, Space and Transport|
|HGF - Program:||Aeronautics|
|HGF - Program Themes:||L AO - Air Traffic Management and Operation|
|DLR - Research area:||Aeronautics|
|DLR - Program:||L AO - Air Traffic Management and Operation|
|DLR - Research theme (Project):||L - Effiziente Flugführung und Flugbetrieb (old)|
|Institutes and Institutions:||Institute of Flight Control > Air traffic systems|
|Deposited By:||Roland Winkler|
|Deposited On:||21 Jul 2011 10:21|
|Last Modified:||19 Jul 2012 12:58|
Repository Staff Only: item control page