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ICONIP
2008
13 years 7 months ago
The Diversity of Regression Ensembles Combining Bagging and Random Subspace Method
Abstract. The concept of Ensemble Learning has been shown to increase predictive power over single base learners. Given the bias-variancecovariance decomposition, diversity is char...
Alexandra Scherbart, Tim W. Nattkemper
ML
2002
ACM
127views Machine Learning» more  ML 2002»
13 years 5 months ago
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
We examine methods for constructing regression ensembles based on a linear program (LP). The ensemble regression function consists of linear combinations of base hypotheses generat...
Gunnar Rätsch, Ayhan Demiriz, Kristin P. Benn...
IFIP12
2004
13 years 7 months ago
Ensembles of Multi-Instance Neural Networks
: Recently, multi-instance classification algorithm BP-MIP and multi-instance regression algorithm BP-MIR both based on neural networks have been proposed. In this paper, neural ne...
Min-Ling Zhang, Zhi-Hua Zhou
PROCEDIA
2010
109views more  PROCEDIA 2010»
13 years 1 months ago
Ridge regression ensemble for toxicity prediction
Traditional methods of assessing chemical toxicity of various compounds require tests on animals, which raises ethical concerns and is expensive. Current legislation may lead to a...
Marcin Budka, Bogdan Gabrys
DMIN
2007
91views Data Mining» more  DMIN 2007»
13 years 7 months ago
Instance Ranking using Ensemble Spread
- This paper investigates a technique for predicting ensemble uncertainty originally proposed in the weather forecasting domain. The overall purpose is to find out if the technique...
Rikard König, Ulf Johansson, Lars Niklasson