DNN Linear Combined Classifier 深度神经网络线性组合分类器
combined classifier of neural network 组合神经网络分类器
In order to improve the performance of the minority class, a combined classifier algorithm is presented based on data pre - processing.
为提高少数类的分类性能，对基于数据预处理的组合分类器算法进行了研究。
The main contribution of this dissertation includes four aspects. They are instantaneous parameters extraction, fuzzy feature selection, single classifier design and combined classifier design.
本文主要工作体现在瞬时参数的提取、模糊特征选择、单个分类器设计和组合分类器设计这四个方面。
A combined classifier is designed. There are two recognition ways used in the classifier. They are the least distance pattern recognition method and the BP neural network pattern recognition method.
设计了一个二级组合分类器，该分类器综合使用了最小距离和BP神经网络两种模式识别方法。
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