loading...
Reduction in Dimensions and Clustering Using Risk and Return Model
Niagara Falls, Ontario, Canada May 21-May 23
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AINAW.2007.30821st International Conference on Adva ...
 This Article 
 
PDF
HTML
IEEE Xplore Subscribers
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Sayed W. Qaiyumi, University of London, UK
Daniel Stamate, University of London, UK
We introduce a new approach of reducing dimensions and clustering of a database, inspired from a computational model used to evaluate economical parameters. This computational model is based on two well known methods for the valuation of assets, namely the Dividend Valuation Model (DVM) and the Capital Asset Pricing Model (CAPM). The model we introduce is called the Risk and Return Model (RRM), and the technique of dimensions reduction is based on calculating the highest risk or in other words the lowest return associated with each attribute/ column in the database. The attributes with the highest risk or lowest return grades are reduced. We have applied a model similar to DVM to cluster the dimensionally reduced data.
Citation:
Sayed W. Qaiyumi, Daniel Stamate, "Reduction in Dimensions and Clustering Using Risk and Return Model," ainaw, vol. 1, pp.373-378, 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07), 2007
Usage of this product signifies your acceptance of the Terms of Use.