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ICML
2004
IEEE
14 years 2 months ago
Ensembles of nested dichotomies for multi-class problems
Nested dichotomies are a standard statistical technique for tackling certain polytomous classification problems with logistic regression. They can be represented as binary trees ...
Eibe Frank, Stefan Kramer
AUSAI
2008
Springer
13 years 10 months ago
Additive Regression Applied to a Large-Scale Collaborative Filtering Problem
Abstract. The much-publicized Netflix competition has put the spotlight on the application domain of collaborative filtering and has sparked interest in machine learning algorithms...
Eibe Frank, Mark Hall
AI
2002
Springer
13 years 8 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
ICML
2006
IEEE
14 years 9 months ago
Kernelizing the output of tree-based methods
We extend tree-based methods to the prediction of structured outputs using a kernelization of the algorithm that allows one to grow trees as soon as a kernel can be defined on the...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
ML
2002
ACM
145views Machine Learning» more  ML 2002»
13 years 8 months ago
Boosting Methods for Regression
In this paper we examine ensemble methods for regression that leverage or "boost" base regressors by iteratively calling them on modified samples. The most successful lev...
Nigel Duffy, David P. Helmbold