104 search results - page 4 / 21 » Iterative Subgraph Mining for Principal Component Analysis |
CORR
2010
Springer
13 years 7 months ago
2010
Springer
Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like ...
AMCS
2008
13 years 7 months ago
2008
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance...
PAMI
2008
13 years 7 months ago
2008
In data-analysis problems with a large number of dimension, principal component analysis based on L2-norm (L2PCA) is one of the most popular methods, but L2-PCA is sensitive to out...
SGAI
2005
Springer
14 years 1 months ago
2005
Springer
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...
APPT
2005
Springer
14 years 1 months ago
2005
Springer
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...