1) Agglomerative Fuzzy K-means
凝聚模糊K-means
1.
Agglomerative Fuzzy K-means proposed by Li Mark can avoid the problems.
Li Mark提出的凝聚模糊K-means算法可以有效的避免这两个问题。
2) fuzzy K-harmonic means
模糊K-harmonic means
1.
A spectral clustering algorithm based on fuzzy K-harmonic means
基于模糊K-harmonic means的谱聚类算法
3) K-means clustering
K-means聚类
1.
More effective algorithm for K-means clustering;
求解K-means聚类更有效的算法
2.
Research on segmenting color regions in textile printing image based on K-means clustering;
基于K-means聚类的纺织品印花图像区域分割
3.
Collaborative filtering recommendation model based on effective dimension reduction and K-means clustering
一种结合有效降维和K-means聚类的协同过滤推荐模型
4) K-Means cluster
K-Means聚类
1.
This paper adopted K-Means cluster to undertake spatio-temporal analysis of the number of tourists in Yancheng eco-tourism area for David s deer.
本文采用K-Means聚类法对盐城麋鹿生态旅游区游客数进行时空聚类,分别从省内和国内(省际)两个尺度上讨论了麋鹿生态旅游区游客变化的阶段性和市场划分,结果表明,1998~2005年间省内旅游流和国内(省际)旅游流从时间上可分为三个阶段,并较好地划分出了四种不同的客源地类型。
2.
Aiming at the high risk of customer loan contract violation in bank enterprise,combining a characteristic analysis model in economics with K-MEANS cluster algorithm in data mining,this paper carries on customer credit rating by using existing customer materials,thus realizing the high quality management of customer information,reducing the risk of bank loans.
针对银行业中客户贷款契约违约风险较高的问题,通过把经济学中的特征分析模型与数据挖掘中的K-MEANS聚类算法相结合,利用现有客户资料,对客户资信评级分类,从而实现对客户信息的高质量管理,降低银行对客户贷款的风险。
5) fuzzy C-means
模糊C-Means
6) K-means clustering algorithm
K-means聚类算法
1.
Research on a method for building up a patent map based on k-means clustering algorithm
基于k-means聚类算法的专利地图制作方法研究
2.
In order to obtain better clustering results,after analyzing the advantages and disadvantages of hierarchical and k-means clustering algorithms,a new algorithm which combines the advantages of hierarchical and k-means clustering algorithms is proposed.
改进算法将分层聚类和k-means聚类算法的优点相结合,首先采用分层聚类,得到一个初始的聚类结果,然后应用k-means聚类算法继续聚类。
3.
The complexity of time and spatial is becoming the difficulty of K-Means clustering algorithm while it deals with the huge amounts of data sets.
K-Means聚类算法在面对海量数据时,时间和空间的复杂性已成为K-Means聚类算法的瓶颈。
补充资料：凝聚
凝聚
coagulation
n ing}U凝聚(eoagulation)矿物悬浮液中添加无机电解质后产生的矿粒聚结现象。相同矿物颗粒之间的凝聚称为同相凝聚;不同矿物颗粒之间的凝聚称为异相凝聚。无机电解质的作用是使矿粒表面双电层压缩，电动电位下降，粒子间静电斥力减小，从而导致分散体系的凝聚。一般情况下矿物悬浮液在酸性介质中易产生凝聚，在碱性介质特别是强碱性介质中易产生分散。这是因为在碱性介质中矿物表面经常带高的负电位，介质pH值越高负电位值越大，矿浆分散性越稳定。实践中矿物悬浮液的凝聚是无选择性的，利用选择性凝聚不易实现矿物之间的分离，因为凝聚过程易受一些外界因素的干扰，分离的条件难于准确控制。在浮选中要尽量避免微细粒矿物间的异相凝聚，减少细粒间的相互混杂和矿泥覆盖，以利于实现有效分离。但在选矿产品脱水处理时，凝聚可加速细粒沉降，强化固液分离。 (龚焕高)
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条