TY - GEN
T1 - Dynamically weighted majority voting for incremental learning and comparison of three boosting based approaches
AU - Gangardiwala, Aliasgar
AU - Polikar, Robi
PY - 2005
Y1 - 2005
N2 - We have previously introduced Learn++, an ensemble based incremental learning algorithm for acquiring new knowledge from data that later become available, even when such data introduce new classes. In this paper, we describe a modification to this algorithm, where the voting weights of the classifiers are updated dynamically based on the location of the test input in the feature space. The new algorithm provides improved performance, stronger immunity to catastrophic forgetting and finer balance to the stability-plasticity dilemma than its predecessor, particularly when new classes are introduced. The modified algorithm and its performance, as compared to Adaboost.M1 and the original Learn++, on real and benchmark datasets are presented.
AB - We have previously introduced Learn++, an ensemble based incremental learning algorithm for acquiring new knowledge from data that later become available, even when such data introduce new classes. In this paper, we describe a modification to this algorithm, where the voting weights of the classifiers are updated dynamically based on the location of the test input in the feature space. The new algorithm provides improved performance, stronger immunity to catastrophic forgetting and finer balance to the stability-plasticity dilemma than its predecessor, particularly when new classes are introduced. The modified algorithm and its performance, as compared to Adaboost.M1 and the original Learn++, on real and benchmark datasets are presented.
UR - http://www.scopus.com/inward/record.url?scp=33745950074&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33745950074&partnerID=8YFLogxK
U2 - 10.1109/IJCNN.2005.1556012
DO - 10.1109/IJCNN.2005.1556012
M3 - Conference contribution
AN - SCOPUS:33745950074
SN - 0780390482
SN - 9780780390485
T3 - Proceedings of the International Joint Conference on Neural Networks
SP - 1131
EP - 1136
BT - Proceedings of the International Joint Conference on Neural Networks, IJCNN 2005
T2 - International Joint Conference on Neural Networks, IJCNN 2005
Y2 - 31 July 2005 through 4 August 2005
ER -