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» Computing LTS Regression for Large Data Sets
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ICML
2005
IEEE
14 years 8 months ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski
APVIS
2007
13 years 9 months ago
Interpreting large visual similarity matrices
Visual similarity matrices (VSMs) are a common technique for visualizing graphs and other types of relational data. While traditionally used for small data sets or well-ordered la...
Christopher Mueller, Benjamin Martin, Andrew Lumsd...
PAMI
1998
88views more  PAMI 1998»
13 years 7 months ago
Large-Scale Parallel Data Clustering
—Algorithmic enhancements are described that enable large computational reduction in mean square-error data clustering. These improvements are incorporated into a parallel data-c...
Dan Judd, Philip K. McKinley, Anil K. Jain
ICDM
2006
IEEE
76views Data Mining» more  ICDM 2006»
14 years 1 months ago
A Probabilistic Ensemble Pruning Algorithm
An ensemble is a group of learners that work together as a committee to solve a problem. However, the existing ensemble training algorithms sometimes generate unnecessary large en...
Huanhuan Chen, Peter Tiño, Xin Yao
BMCBI
2007
136views more  BMCBI 2007»
13 years 7 months ago
Prediction of tissue-specific cis-regulatory modules using Bayesian networks and regression trees
Background: In vertebrates, a large part of gene transcriptional regulation is operated by cisregulatory modules. These modules are believed to be regulating much of the tissue-sp...
Xiaoyu Chen, Mathieu Blanchette