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APPT
2005
Springer
14 years 3 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 3 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...
IWINAC
2005
Springer
14 years 3 months ago
Separation of Extracellular Spikes: When Wavelet Based Methods Outperform the Principle Component Analysis
spike separation is a basic prerequisite for analyzing of the cooperative neural behavior and neural code when registering extracelluIarly. Final performance of any spike sorting m...
Alexey N. Pavlov, Valeri A. Makarov, Ioulia Makaro...
SGAI
2005
Springer
14 years 3 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...
ICSR
2004
Springer
14 years 3 months ago
Feature Dependency Analysis for Product Line Component Design
Analyzing commonalities and variabilities among products of a product line is an essential activity for product line asset development. A feature-oriented approach to commonality a...
Kwanwoo Lee, Kyo Chul Kang