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CSDA
2011
13 years 2 months ago
Mapping electron density in the ionosphere: A principal component MCMC algorithm
The outer layers of the Earth’s atmosphere are known as the ionosphere, a plasma of free electrons and positively charged atomic ions. The electron density of the ionosphere var...
Eman Khorsheed, Merrilee Hurn, Christopher Jenniso...
NIPS
2007
13 years 9 months ago
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression
We propose a method for reconstruction of human brain states directly from functional neuroimaging data. The method extends the traditional multivariate regression analysis of dis...
Sennay Ghebreab, Arnold W. M. Smeulders, Pieter W....
ADBIS
2003
Springer
108views Database» more  ADBIS 2003»
14 years 26 days ago
Dynamic Integration of Classifiers in the Space of Principal Components
Recent research has shown the integration of multiple classifiers to be one of the most important directions in machine learning and data mining. It was shown that, for an ensemble...
Alexey Tsymbal, Mykola Pechenizkiy, Seppo Puuronen...
APWEB
2005
Springer
14 years 1 months ago
An Incremental Subspace Learning Algorithm to Categorize Large Scale Text Data
The dramatic growth in the number and size of on-line information sources has fueled increasing research interest in the incremental subspace learning problem. In this paper, we pr...
Jun Yan, QianSheng Cheng, Qiang Yang, Benyu Zhang
PAKDD
2005
ACM
164views Data Mining» more  PAKDD 2005»
14 years 1 months ago
Covariance and PCA for Categorical Variables
Covariances from categorical variables are defined using a regular simplex expression for categories. The method follows the variance definition by Gini, and it gives the covaria...
Hirotaka Niitsuma, Takashi Okada