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AAAI
1997
13 years 11 months ago
An Empirical Evaluation of Bagging and Boosting
Richard Maclin, David W. Opitz
COGSCI
2007
85views more  COGSCI 2007»
13 years 9 months ago
Semantic Boost on Episodic Associations: An Empirically-Based Computational Model
Words become associated following repeated co-occurrence episodes. This process might be further determined by the semantic characteristics of the words. The present study focused...
Yaron Silberman, Shlomo Bentin, Risto Miikkulainen
ROCAI
2004
Springer
14 years 3 months ago
An Empirical Evaluation of Supervised Learning for ROC Area
We present an empirical comparison of the AUC performance of seven supervised learning methods: SVMs, neural nets, decision trees, k-nearest neighbor, bagged trees, boosted trees,...
Rich Caruana, Alexandru Niculescu-Mizil
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
12 years 5 days ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
ICML
2005
IEEE
14 years 10 months ago
A smoothed boosting algorithm using probabilistic output codes
AdaBoost.OC has shown to be an effective method in boosting "weak" binary classifiers for multi-class learning. It employs the Error Correcting Output Code (ECOC) method...
Rong Jin, Jian Zhang