A method to predict the subcellular location of proteins is proposed based on the LZ complexity similarity of symbolic sequences and K nearest neighbor rule.
提出了一个基于符号序列LZ复杂性相似度和K近邻规则的蛋白质亚细胞位点类型预测的方法。
Because precise determination of a computer virus is undecidable, a method based on improved K-nearest neighbor to detect computer virus approximately is presented in this paper.
由于计算机病毒检测的不可判定性，提出了一种基于改进的K最近邻检测方法来实现对计算机病毒的近似判别。
This paper put forward and carried out a text classification method using feed-forward neural network and K-nearest neighbor.
提出并实现了一种结合前馈型神经网络和K最近邻的文本分类算法。
In the process of researching post-classification comparison method this paper improve K-nearest neighbor classifier and gain better detection result.
在分类结果比较法的研究过程中，针对城区变化检测的特定问题，改进了经典k近邻法，获得了较好的变化检测结果。
Combining this method with the K-nearest neighbor decision rule, a fixed neighborhood, decision algorithm is developed.
将该方法与K—最近邻判决规则结合，提出了用于判别的固定邻域判决算法。
At the same time, testing the order by K-nearest neighbor classifier which is also comes from data mining and the result proves the correctness and feasibility of this method.
同时，运用数据挖掘中的K -最临近分类方法对所得出的强弱顺序进行测试，结果表明了这种区分方法的正确性、可行性。
At the same time, testing the order by K-nearest neighbor classifier which is also comes from data mining and the result proves the correctness and feasibility of this method.
同时，运用数据挖掘中的K -最临近分类方法对所得出的强弱顺序进行测试，结果表明了这种区分方法的正确性、可行性。
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