1051 search results - page 20 / 211 » An algorithm for the principal component analysis of large d... |
NIPS
2000
13 years 9 months ago
2000
A central issue in principal component analysis (PCA) is choosing the number of principal components to be retained. By interpreting PCA as density estimation, this paper shows ho...
AMSTERDAM
2009
13 years 5 months ago
2009
The paper presents a statistical evaluation of the typological data about color naming systems across the languages of the world that have been obtained by the World Color Survey....
ICNS
2007
IEEE
14 years 2 months ago
2007
IEEE
In this paper, the problem of discovering anomalies in a large-scale network based on the data fusion of heterogeneous monitors is considered. We present a classification of anoma...
SSDBM
2008
IEEE
14 years 2 months ago
2008
IEEE
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
CSB
2003
IEEE
14 years 1 months ago
2003
IEEE
The problem of clustering continuous valued data has been well studied in literature. Its application to microarray analysis relies on such algorithms as -means, dimensionality re...