cluster process中文是什么意思

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中文翻译
造句

[数] 簇生过程

a cluster 自力村碉楼群
a cluster of 一串/丛; 一串，一束，一群; 一群、一组; 一群；一组
cluster n. 1.丛集；丛；(葡萄等的)串，挂；(花)团；(秧)蔸；组。 2.(蜂、人等的)丛，群，群集。 3.【物理学】聚集，组件；【化学】类族，基；(原子)团；【天文学】星团。 4.【美军】(表示又一个同等勋章的)金属片。 5.【语音】音丛，音群，义丛，词组。 6.集中建筑群〔在一大片土地上集中兴建住宅，以提供较大的公共休息场所〕。 in a cluster 成串的；成团[群]的。 vi.,vt. (使)成群；(使)群集。 clustered column 【建筑】簇柱。
a cluster of buildings 一群建筑物
a cluster of butterflies 一群蝴蝶
a cluster of flaws 密集区缺陷
a cluster of grapes 葡萄
a cluster of islands 一群海岛
a cluster of stars 一个星团
abell cluster 阿贝尔星系团
aggression cluster 精神冲击弹
arches cluster 圆拱星团
argolis cluster 阿勾里斯星群
aromatic cluster 芳香族稠环
artificial cluster 人为群体
association cluster 关联簇
atas cluster 先进技术通报系统处
atom cluster 金属胶态原子簇
attitude cluster 态度丛
banana cluster 香蕉串
barchan cluster 新月沙丘群
barrel cluster 炮管组
base cluster 基簇; 基组
beehive cluster 鬼星团
bezel cluster 表框

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例句与用法

Birch algorithm . density-based method : if the density of neighborhood, that is the number of data objects, exceeds a certain value, the clustering process will be continued
基于密度的方法的主要思想是：只要邻近区域的密度(对象或数据点的数目)超过某个阈值，就继续聚类。
Dissimilarities are assessed base on the attribute values describing the objects . clustering processes are always carried out in the condition without pre-known knowledge, so the main task is to solve that how to get the clustering result in this premise
聚类分析依据的原则是使同一聚簇中的对象具有尽可能大的相似性，而不同聚簇中的对象具有尽可能大的相异性，聚类分析主要解决的问题是如何在没有先验知识的前提下，实现满足这种要求的聚簇的聚合。
However, there have still some unresolved problems : first, how to determine the number and size of the clusters automatically during the clustering process . second, how to utilize the " local " ridge regression method which including multiple regularization parameters in learning rbf network . third, those clusters in irregular form ca n't represented by radial basis function, thus we must find some other basis functions that can describe the irregular form
但是仍然存在几个问题尚待解决：首先，聚类时怎样自动确定簇的个数和半径；其次，如何利用含有多个正规化参数的局部岭回归方法进行rbf网络学习；第三，如果簇的形状是不规则的，则它很难用径向基函数来描述，因此需要研究其它能代表不规则形状的簇的基函数。
Clustering analysis is the method which partition class to the clustered objects as required of thing's characteristics . clustering processes are always carried out in the condition with no pre-known knowledge, so the most research task is to solve that how to get the clustering result in this premises
聚类分析是在没有先验知识支持的前提下,根据事物本身的特性研究被聚类对象的类别划分,实现满足这种要求的类的聚合,它所依据的原则是使同一类中的对象具有尽可能大的相似性,而不同类中的对象具有尽可能大的差异性。
clustering processes are always carried out in the condition with no pre-known knowledge, so the most research task is to solve that how to get the clustering result in th is premise . as the development of data mining, a number of clustering algorithms has been founded, in general, major clustering methods, can be classified into the following categories : partitioning methods; hierarchical methods; density-based methods; grid-based methods; model-methods; besides these, some clustering algorithms integrate the ideas of several clustering methods
正是由于聚类分析的重要性和特殊性，近年来在该领域的研究取得了长足的发展，涌现出了许多聚类分析的方法，如划分聚类方法(partitioningmethod)、层次聚类方法(hierarchicalmethod)、基于密度(density?based)的聚类方法、基于网格(grid?based)的聚类方法、基于模型(model?based)的聚类方法等等。
And it adds a-priori information into the patterns to change the method as a semi-supervised clustering . in the clustering process, the unlabelled patterns compare similarities with the labeled patterns, and then the accuracy of the algorithm can be increased . ( 3 ) the paper proposes an interactive learning-based image mining in remote sensing
由于遥感图像各类别在特征空间中散点图的分布的特点,本文对传统的fcm聚类算法进行改进,并且加入先验信息之后,将原来的非监督的聚类变成一种半监督的聚类方法,通过与已标签的样本进行相似性比较,能有效地提高聚类算法的准确度。