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APPT
2005
Springer
14 years 1 months ago
Principal Component Analysis for Distributed Data Sets with Updating
Identifying the patterns of large data sets is a key requirement in data mining. A powerful technique for this purpose is the principal component analysis (PCA). PCA-based clusteri...
Zheng-Jian Bai, Raymond H. Chan, Franklin T. Luk
EWMF
2005
Springer
14 years 1 months ago
Discovering a Term Taxonomy from Term Similarities Using Principal Component Analysis
Abstract. We show that eigenvector decomposition can be used to extract a term taxonomy from a given collection of text documents. So far, methods based on eigenvector decompositio...
Holger Bast, Georges Dupret, Debapriyo Majumdar, B...
SGAI
2005
Springer
14 years 1 months ago
The Effect of Principal Component Analysis on Machine Learning Accuracy with High Dimensional Spectral Data
This paper presents the results of an investigation into the use of machine learning methods for the identification of narcotics from Raman spectra. The classification of spectr...
Tom Howley, Michael G. Madden, Marie-Louise O'Conn...
CORR
2010
Springer
160views Education» more  CORR 2010»
13 years 7 months ago
PCA 4 DCA: The Application Of Principal Component Analysis To The Dendritic Cell Algorithm
As one of the newest members in the field of artificial immune systems (AIS), the Dendritic Cell Algorithm (DCA) is based on behavioural models of natural dendritic cells (DCs). U...
Feng Gu, Julie Greensmith, Robert Oates, Uwe Aicke...
IPAS
2010
13 years 5 months ago
An unsupervised learning approach for facial expression recognition using semi-definite programming and generalized principal co
In this paper, we consider facial expression recognition using an unsupervised learning framework. Specifically, given a data set composed of a number of facial images of the same...
Behnood Gholami, Wassim M. Haddad, Allen Tannenbau...