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» Improved independent component regression modeling
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CDC
2009
IEEE
155views Control Systems» more  CDC 2009»
13 years 9 months ago
Improved independent component regression modeling
The conventional independent component regression (ICR), as an exclusive two-step implementation algorithm, has the risk similar to principal component regression (PCR). That is, t...
Chunhui Zhao, Furong Gao, Tao Liu, Fuli Wang
CSDA
2010
172views more  CSDA 2010»
13 years 5 months ago
Testing for two components in a switching regression model
We consider switching regression models with independent or Markov-dependent regime. Based on the modified likelihood ratio test (LRT) statistic by Chen, Chen and Kalbfleisch (200...
Jörn Dannemann, Hajo Holzmann
IPMI
2005
Springer
13 years 10 months ago
Automatic Prediction of Myocardial Contractility Improvement in Stress MRI Using Shape Morphometrics with Independent Component
Abstract. An important assessment in patients with ischemic heart disease is whether myocardial contractility may improve after treatment. The prediction of myocardial contractilit...
Avan Suinesiaputra, Alejandro F. Frangi, Hildo J. ...
SDM
2008
SIAM
144views Data Mining» more  SDM 2008»
13 years 6 months ago
Active Learning with Model Selection in Linear Regression
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Masashi Sugiyama, Neil Rubens
CSDA
2006
304views more  CSDA 2006»
13 years 5 months ago
Using principal components for estimating logistic regression with high-dimensional multicollinear data
The logistic regression model is used to predict a binary response variable in terms of a set of explicative ones. The estimation of the model parameters is not too accurate and t...
Ana M. Aguilera, Manuel Escabias, Mariano J. Valde...