94 search results - page 2 / 19 » The Random Subspace Method for Constructing Decision Forests |
IJAR
2010
13 years 3 months ago
2010
Following Breiman’s methodology, we propose a multi-classifier based on a “forest” of randomly generated fuzzy decision trees, i.e., a Fuzzy Random Forest. This approach co...
ICDAR
2007
IEEE
13 years 11 months ago
2007
IEEE
In the Pattern Recognition field, growing interest has been shown in recent years for Multiple Classifier Systems and particularly for Bagging, Boosting and Random Subspaces. Th...
ICONIP
2008
13 years 6 months ago
2008
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...
ILP
2004
Springer
13 years 10 months ago
2004
Springer
Random forest induction is a bagging method that randomly samples the feature set at each node in a decision tree. In propositional learning, the method has been shown to work well...
JAIR
2008
13 years 4 months ago
2008
In this paper, we show that a continuous spectrum of randomisation exists, in which most existing tree randomisations are only operating around the two ends of the spectrum. That ...