1) weighted nearest neighbor
加权最近邻
1.
It established different NCs based on bootstrapping technique,and evaluated the classification accuracy of every NC by different sorts of weighted nearest neighbors for mixed attributes,then the NCs with low relative generalization error rates were dynamically selected and majority voting was applied to those NCs in order to conduct the final classification results of the ensemble.
基于bootstrapp ing构建不同的个体神经网络,针对混合属性,通过不同的加权最近邻设计评估单个网络的分类精度,在此基础上动态选择误差率较小的神经网络,经过投票形成集成分类结果。
2) k-nearest neighbour weights
k-最邻近权
3) weighted knearest neighborhood
加权K近邻
1.
In this paper, based on the characteristics of data set, we put forward weighted knearest neighborhood method.
本文根据数据的特点,改进了传统的K近邻方法,提出了加权K近邻的方法,进一步增强了利用测井数据识别岩性的能力,并在实际应用中证明了本方法的正确性和实用性。
4) fuzzy kernel weighted nearest prototype classifier
模糊核加权最近邻近分类器
5) Wavelt packets decomposition
加权K近邻法
6) nearest neighbors
最近邻近
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