knn

This method first calculated the degree matrix of membership using the fuzzy KNN method .

该方法首先通过基于模糊的KNN方法求出隶属度函数矩阵；

K Nearest Neighbor ( KNN ) Method Used in Feature Selection

用于特征筛选的最近邻（KNN）法

In this paper , we proposed an automatic keyword extraction method based on KNN method .

本文利用K最近邻方法的思想，提出了一种基于K最近邻的关键词自动抽取方法。

It plays an instructional role in academic study and practical application of KNN text classification algorithm .

对KNN文本分类算法的理论研究和实际应用起了指导作用。

The traditional method about KNN is generally used Euclidean distance formula to measure the distance between the two samples .

传统的KNN算法一般采用欧式距离公式度量两样本间的距离。

K nearest neighbor ( kNN ) query is one of the fundamental issues in spatial database research area .

k最近邻居问题（kNN）是空间数据库研究领域最基本的问题之一，是指在特定空间中寻找离查询点最近的k个目标点，包括几何空间，道路空间等。

KNN ( K nearest neighbors ) is one of the best text categorization algorithms based on Vector Space Model .

K近邻算法是基于向量空间模型的最好的文本分类算法之一。

In the paper , what is the typical sample of KNN is analyzed , and a method of samples selection based density is presented .

论文针对KNN这种常用的文本分类方法，分析了什么是它的典型样本，提出了一种基于密度的样本选择算法。

The results are compared with the genetic algorithm in combination with the k-nearest neighbor ( KNN ) classification rule .

最后，将比较的结果再与基因演算法结合k个最近邻法进行比较。

To improve the classification performance , this article puts forward the multi level feature selection method and the kernel based distance weighted KNN algorithm .

为了提高分类性能，本文提出了中文文本多层次特征提取方法和基于核的距离加权KNN算法。

You can change the " KNN "( K-nearest neighbors ) to be anything you want .

可以任意更改“KNN”（K-最近邻）。

In this paper we present a large margin feature weighting method for k - nearest neighbor ( kNN ) classifier .

我们的工作是，针对k近邻分类器提出一种大边界特征加权算法。

KNN is one of top performers , and it performs well in scaling up to very large and noisy classification problems .

KNN是最性能最优的方法，它在处理增加到非常大和杂乱的问题时成效最显著。

AIRS results in the memory cell pool after it is trained and classifies the original antigens by KNN .

AIRS通过训练产生记忆细胞池，利用最近邻原理对原始抗原分类。

Especially , it discusses some key techniques such as web page classification model , purity of web page , weight of feature , KNN classification .

描述了一个完整的中文网页分类系统的设计和实现过程，重点介绍了网页分类中的网页净化、特征加权、KNN分类等关键技术。

One search Model is based on BP neural network and another based on K-Nearest-Neighbor ( KNN ) algorithm , a dynamic weight tuning algorithm is proposed .

基于BP神经网络的检索模型和基于最近邻居法的检索模型，并给出了一种权重动态调节方法；

Improved KNN algorithm by using the combination technology , and applied it to the forecast of non-mining fracture of shaft-lining of mine .

利用组合技术对KNN算法进行改进，并将其应用于煤矿立井井筒非采动破裂的预测。

The main point of this program is based on pattern recognition techniques , the chief structure feature of an unknown can be obtained from the KNN classification results .

本程序主要是以模式识别技术为基础，实现了对未知物谱图的KNN分类，进而得到未知物的主要结构特征。

Feature weighting is one of the important problems for feature weighting based KNN algorithm , and many heuristic methods have been employed to solve the problem traditionally .

特征权重学习是基于特征赋权的K近邻算法需要解决的重要问题之一，传统上提出了许多启发式的学习方法。

The KNN Media Center is a new landmark broadcast headquarters and cultural media facility located in Busan 's Centum City .

在最近邻媒体中心是一个新的里程碑广播总部和文化传媒设施，釜山的多功能城市位置。

Experimental results show that B-KNN method remarkably outperforms KNN method , and it is more suitable for classification tasks with deep hierarchy categorization space .

实验结果表明，与KNN相比，B-KNN的性能有较大提升，更适用于具有较深层次类型空间的文本分类应用。

A new method for fault diagnosis of large-scale analogue circuits with tolerance based on body algorithm and Kohonen neural networks ( KNN ) is presented in the paper .

提出了一种基于集团法和自组织神经网络的容差电路故障诊断方法。

This paper introduces an effect query algorithm based on TPR tree , such algorithm can support kNN query for moving objects and has a better performance than known algorithms .

该文在TPR树这一时空索引的基础上，提出了一种高效的最近邻查询算法，能够支持移动对象的多个最近邻对象的查询，并在性能上也有所提高。

The emphasis of this paper is a method based on the contents & KNN . A furthermore experiment tests the effects of the categorization techniques of Chinese Web texts .

最后通过实验测试了使用KNN算法的中文Web文本分类技术的效果。

For the former , a processing measure based on strategy pattern is offered , which achieves three kinds of algorithm : simple processing , KNN and DTB .

针对缺损数据提出了基于策略模式的缺损数据处理方法，该方法利用具体的策略类实现了简单处理、KNN和DTB三种缺损数据处理算法；

This paper introduces the flow of Chinese text classification and relevant technologies , and an improved KNN method is proposed on the basis of analyzing the disadvantage of traditional KNN method .

介绍了基于KNN方法的中文文本分类流程及相关技术，在分析传统KNN方法不足的基础上提出一种改进的KNN方法。

To improve the design of classifier and training time , a new method combining the clonal selection algorithm and K nearest neighbor ( CSA + KNN ) is proposed .

针对植物叶片识别中分类器设计和训练识别时间较长的问题，提出了一种基于克隆选择算法和K近邻判别分析（CSA+KNN）的叶片识别方法。

The kernel based weighted KNN algorithm solves the multi peak distribution problem and the overlap boundary problem of the sample set , as well as the classifier 's precise decision problem .

基于核的距离加权KNN算法解决了样本的多峰分布、边界重叠问题和分类器的精确分类决策问题。

This paper implemented an improved K-Nearest Neighbor ( Fuzzy KNN ) algorithm in which Fuzzy Adaptive Resonance Theory ( ART ) is applied in K-NN classification to make a new algorithm .

提出了一种K-最近邻改进算法，该算法用模糊自适应共振理论（FuzzyART）对K-最近邻的训练样本集进行浓缩，以改善K-最近邻的计算速度。

Obviously , the experimental result shows that , in multi-level decomposition , the method is better than the traditional Bayes and K-Nearest Neighbor ( KNN ) classification in recognition rate .

实验结果显示，该方法在多层小波分解的情况下，对于少数民族文种识别的精度好于传统的贝叶斯和KNN。