TY - GEN
T1 - Constructing weak learner and performance evaluation in AdaBoost
AU - Zhou, Mian
AU - Wei, Hong
PY - 2009
Y1 - 2009
N2 - This paper gives a deep investigation into AdaBoost algorithm, which is used to boost the performance of any given learning algorithm. Within AdaBoost, weak learners are crucial and primitive parts of the algorithm. Since weak learners are required to train with weights, two types of weak learners: Artificial Neural Network weak learner and naive Bayes weak learner are designed. The results show AdaBoost by naive Bayes weak learners is superior to Artificial Neural Network weak learners, it shares the same generalisation ability with Support Vector Machine.
AB - This paper gives a deep investigation into AdaBoost algorithm, which is used to boost the performance of any given learning algorithm. Within AdaBoost, weak learners are crucial and primitive parts of the algorithm. Since weak learners are required to train with weights, two types of weak learners: Artificial Neural Network weak learner and naive Bayes weak learner are designed. The results show AdaBoost by naive Bayes weak learners is superior to Artificial Neural Network weak learners, it shares the same generalisation ability with Support Vector Machine.
UR - http://www.scopus.com/inward/record.url?scp=77949678234&partnerID=8YFLogxK
U2 - 10.1109/CISE.2009.5362581
DO - 10.1109/CISE.2009.5362581
M3 - Conference Proceeding
AN - SCOPUS:77949678234
SN - 9781424445073
T3 - Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009
BT - Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009
T2 - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009
Y2 - 11 December 2009 through 13 December 2009
ER -