The fuzzy c-means algorithm (FCM) is one of widely used clustering algorithms.
模糊c均值算法(FCM)是经常使用的聚类算法之一。
So this paper will discuss that how to enhance the clustering algorithms' accuracy.
所以，本文就如何提高聚类算法的聚类准确性进行了研究。
In this paper, we analyses why the clustering algorithms are put out in Ad Hoc Networks.
分析了无线自组织网中的分群算法提出的原因，介绍了目前分群算法的基本思想、类型和特点。
DBSCAN algorithm is an outstanding representative of density based on clustering algorithms.
DBSCAN是基于密度的聚类算法的一个典型代表。
Some classical clustering algorithms and decision trees algorithms are analyzed and compared.
并具体分析比较了多种的典型聚类和决策树数据挖掘算法。
Research on grid clustering algorithms has become a highly active topic in the data mining research.
网格聚类算法研究已经成为数据挖掘研究领域中非常活跃的一个研究课题。
Most clustering algorithms can not meet the demand of speed and self-adapting about text clustering.
目前多数聚类算法不能很好地适应文本聚类的快速自适应需求。
The common clustering algorithms in mobile Ad Hoc network (MANET) are firstly analyzed in this paper.
分析了几种常见分簇算法，在此基础上提出了一种新的基于移动代理的分簇策略。
This method also complements the shortages of current clustering algorithms in outlier detection and using.
此方法还弥补了现有聚类算法在离群点识别、使用上的缺欠。
Currently, there are some applications of clustering algorithms in customer segmentation of bank for experiments.
目前已有一些聚类算法应用于银行客户细分的实验。
Experiment results indicate that the proposed algorithm outperforms the existing text clustering algorithms in accuracy.
实验表明，该算法与现有的文本聚类算法相比，准确率有一定的提高。
For the lack of valuable prior knowledge in the image retrieval process, unsupervised clustering algorithms should be applied.
因为在对图像进行聚类分析时，通常缺少可资利用的先验知识，所以需要采用无监督的聚类算法。
Mahout provides driver programs for all of the clustering algorithms, including the k-Means algorithm, aptly named the KMeansDriver.
Mahout为所有集群算法都提供了驱动程序，包括k - Means算法，更合适的名称应该是KMeansDriver。
Experimental results show that our algorithm has a better performance on network lifetime than the common clustering algorithms.
实验结果表明，新算法较常见分簇算法更能够延长网络寿命。
To address the deficiencies of most existing gene clustering algorithms, a novel gene projected clustering algorithm is proposed.
针对现有基因投影聚类算法的不足，提出一种有效的基因投影聚类算法。
While a lot of clustering algorithms for data streams have been proposed, they offer no solution to the combination of these requirements.
目前已经提出了许多数据流聚类算法，但是都尚未解决以上数据流环境下的要求。
Then introduces spectral clustering algorithm based on deficiencies of variety of traditional clustering algorithms on intrusion detection.
然后分析了各种传统聚类算法在入侵检测中所表现的不足，并引入了谱聚类算法加以解决。
For many clustering algorithms, it is very important to determine an appropriate number of clusters, which is called cluster validity problem.
对于许多聚类算法，决定合适的聚类数目至关重要，这称为聚类有效性问题。
The pairwise constraints are the most common prior knowledge, and many semi-supervised clustering algorithms are based on the type of constraints.
成对约束是先验知识中最普遍的，目前许多半监督聚类算法都基于此类约束形式。
The combination of the ant clustering technology and the text clustering technology leads to the development of ant-based text clustering algorithms.
蚁群聚类算法与文本聚类技术的结合就形成了基于蚁群的文本聚类算法。
This paper firstly introduces the classification of incremental clustering algorithms and the research state, defines the concept of algorithm equivalence.
本文首先介绍了增量聚类算法的分类以及研究现状，提出了增量聚类算法等价性概念；
Considering fuzzy C-means clustering algorithms are sensitive to initialization and easy fall - en to local minimum, a novel optimization method is proposed.
针对模糊C均值聚类算法对初始值敏感、易陷入局部最优的缺陷，提出一种新的优化方法。
Many new and improved clustering algorithms have been proposed, but it is still hard to find a single algorithm to explore variety of structures of data objects.
尽管目前许多新型或改进的算法被提出，但仍然难以找到一种单一的算法可以探索各种数据对象分布结构。
Firstly, tag 's meaning for user profile is proved, and clustering algorithms based on social tagging from the aspects of users, resources and tags are discussed.
首先是明确了标签对于用户模型的意义，接着，从用户、资源和标签三个角度对基于社会化标注的聚类算法进行了讨论。
The selection of starting center points of clustering has great effects on the constringency speed of this clustering algorithms and the performance of clustering.
聚类初始中心的选择对该聚类算法的收敛速度和聚类的性能都有很大的影响。
Then, three equivalent clustering algorithms are provided for the dataset with fragmentary samples, which decreases the influence of incomplete data on clustering.
提出样本目标值残缺情况下的三种等效聚类算法，可使残缺数据样本有效地参加聚类，减少样本数据残缺对聚类的影响；
On the basis of the analysis and research of traditional clustering algorithms, a clustering algorithm based on density and adaptive density-reachable is presented.
在分析与研究现有聚类算法的基础上，提出一种基于密度和自适应密度可达的改进算法。
This paper studies the clustering algorithms on different perspectives, and analyzes the merits and weaknesses of different types of weighted clustering algorithms.
本文从不同的角度研究移动自组网中基于权值的分簇算法，并对这些算法进行归类和优缺点分析。
An energy balancing distributed clustering algorithm for wireless sensor networks is proposed to solve the problem of imbalance in energy load for clustering algorithms.
为了解决分簇算法中网络节点能量负载不平衡的问题，提出了一种能量均衡的分布式成簇算法。
An energy balancing distributed clustering algorithm for wireless sensor networks is proposed to solve the problem of imbalance in energy load for clustering algorithms.
为了解决分簇算法中网络节点能量负载不平衡的问题，提出了一种能量均衡的分布式成簇算法。
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