Title :
Improving boosting performance with a local combination of learners
Author :
Mayhua-López, Efraín ; Gómez-Verdejo, Vanessa ; Figueiras-Vidal, Aníbal R.
Author_Institution :
Dept. of Signal Theor. & Commun., Univ. Carlos III de Madrid, Leganés, Spain
Abstract :
This work explores the possibility of improving the performance of Real Adaboost ensemble classifiers by replacing their standard linear combination of learners by a gating scheme. This more powerful fusion method is defined following the epoch-by-epoch construction of boosting ensembles. Preliminary experimental results support the potential of this new approach.
Keywords :
learning (artificial intelligence); neural nets; pattern classification; boosting ensembles; boosting performance; epoch-by-epoch construction; gating scheme; real Adaboost ensemble classifiers; standard linear combination; Algorithm design and analysis; Artificial neural networks; Boosting; Cost function; Error analysis; Neurons; Training;
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6916-1
DOI :
10.1109/IJCNN.2010.5596317
