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» VIF Regression: A Fast Regression Algorithm for Large Data
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BMCBI
2008
186views more  BMCBI 2008»
13 years 7 months ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells
KDD
1997
ACM
103views Data Mining» more  KDD 1997»
13 years 11 months ago
Fast Committee Machines for Regression and Classification
In many data mining applications we are given a set of training examples and asked to construct a regression machine or a classifier that has low prediction error or low error rat...
Harris Drucker
CORR
2010
Springer
171views Education» more  CORR 2010»
13 years 6 months ago
Graphical Models Concepts in Compressed Sensing
This paper surveys recent work in applying ideas from graphical models and message passing algorithms to solve large scale regularized regression problems. In particular, the focu...
Andrea Montanari
KDD
2007
ACM
148views Data Mining» more  KDD 2007»
14 years 8 months ago
Scalable look-ahead linear regression trees
Most decision tree algorithms base their splitting decisions on a piecewise constant model. Often these splitting algorithms are extrapolated to trees with non-constant models at ...
David S. Vogel, Ognian Asparouhov, Tobias Scheffer
KDD
2004
ACM
285views Data Mining» more  KDD 2004»
14 years 28 days ago
Effective localized regression for damage detection in large complex mechanical structures
In this paper, we propose a novel data mining technique for the efficient damage detection within the large-scale complex mechanical structures. Every mechanical structure is defi...
Aleksandar Lazarevic, Ramdev Kanapady, Chandrika K...