Title :
Majority vote based on weak classifiers
Author :
Chen, Dechang ; Cheng, Xiuzhen
Author_Institution :
Wisconsin Univ., Green Bay, WI, USA
Abstract :
We present a two-class pattern recognition method through the majority vote which is based on weak classifiers. The weak classifiers are defined in terms of rectangular regions formed by the original training data. Tests on real and simulated data sets show that this classifier combination procedure can lead to a high accuracy
Keywords :
pattern classification; majority vote; rectangular regions; weak classifiers; Bagging; Machine learning; Pattern recognition; Performance evaluation; Testing; Training data; Voting;
Conference_Titel :
Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-5747-7
DOI :
10.1109/ICOSP.2000.893397
