对两种阈值和偏置计算方法的仿真实验结果表明，在错分率降可接受的范围内，二者均使用较少的弱分类器便可获得高识别率的强分类器。
Simulation experiments show when the error rate is in an acceptable range, the algorithms using fewer weak classifiers will be able to guarantee the strong classifier to maintain a high correct rate.
对两种阈值和偏置计算方法的仿真实验结果表明，在错分率降可接受的范围内，二者均使用较少的弱分类器便可获得高识别率的强分类器。
Simulation experiments show when the error rate is in an acceptable range, the algorithms using fewer weak classifiers will be able to guarantee the strong classifier to maintain a high correct rate.
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