Majority vote based on weak classifiers
Dechang Chen, Xiuzhen Cheng · 2000
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.