In the domain of information retrieval, using feature clustering to extract the features is one of the most important means in the reduction of text dimension.
借助特征聚类进行特征抽取是信息检索领域进行文本特征降维的重要手段之一。
Does the clustering feature use Shoal framework?
集群特性使用到Shoal框架了么？
Horizontal clustering is achieved by clustering the queue managers and brokers using the multi-instance feature, which provides the following advantages.
水平集群通过使用多实例特性设置队列管理器和代理的集群来实现，水平集群提供以下好处。
This neural network pattern recognition can be applied to feature extraction, clustering analysis, edge detection, signal enhancement and noise suppression, data compression, such as various links.
这样神经网络可应用于模式识别的特征提取、聚类分析、边缘检测、信号增强以及噪声抑制、数据压缩等各个环节。
The Design Advisor now provides advice on materialized query tables (MQTs), multidimensional clustering tables (MDCs), and Data partitioning Feature (DPF) partitioning keys, in addition to indexes.
除了索引外，Design Advisor还提供关于物化查询表(MQT)、多维集群表(MDC)和数据分区功能(DataPartitioning Feature,DPF)分区键的建议。
Another feature that JBoss has had for at least a couple of years is the clustering and failover feature.
JBoss已经具备了至少两年的另一个功能是群集和故障转移。
With the clustering feature analyzed, restrained function and pattern similarity are introduced. Then the algorithm of improved FCM is presented.
通过对模糊c均值算法聚类特性的分析，引入了约束函数及模式相似度的概念，提出了改进的FCM算法。
There are four part of it: image input, dealing with image feature, clustering and choosing the best and output the result.
框架由四部分组成：图像输入阶段、图像特征处理阶段、聚类择优阶段和最后的分割结果。
A stochastic clustering method based on pairwise similarity of elements was utilized to cluster feature space.
利用基于元素间相似性的随机聚类方法对特征空间进行聚类。
A method that applies the clustering function of SOFM (Self-Organizing Feature Maps) network is proposed for autonomous star pattern recognition.
介绍了一种利用自组织特征映射(SOFM)网络的聚类功能进行全天星图识别的方法。
An autonomous star pattern recognition method using the tri-star clustering function of SOFM (Self-Organizing Feature Maps) network is described.
介绍了一种利用SOFM(自组织特征映射)网络的聚类功能进行全天星图识别的算法。
The algorithm divides tag co -occurrence network based on tag node's centrality and similarity, and automatically generates a cluster feature tag after clustering to represent that cluster.
算法基于标签节点的核心度和相似性对标签共现网络进行分割，并在聚类后自动生成该类的特征标签来代表该类簇。
MFCC USES intermediate clustering results in one type of feature space to help the selection in other types of feature Spaces.
MFCC充分利用了一个特征空间的中间聚类结果来帮助另一个特征空间进行特征选择。
This model can transform units bidding curve of power producer in market into a one-dimensional feature vector, so it can implement classification of units bidding using classical clustering method.
利用平均电价差值积分模型将电力市场中发电商的机组报价曲线转换为一维特征向量，从而采用传统聚类方法对机组报价曲线实现分类。
Mathematical programming is important in feature selection, clustering and regression, and these are the problems, which are solved imminently.
数学规划在特征提取、聚类和回归等方面有很重要的应用，而这些都是数据挖掘亟待解决的问题。
Computing method of weighted value for feature item based on text representation can determine extraction of text feature, which have influence on accuracy of the text clustering.
文本表示中特征项的权值计算方法决定了文本特征的提取，在很大程度上影响了文本聚类的准确率。
In this paper, the basic principle of the clustering algorithm based on self-organizing feature map network is discussed, and pointed out its defects.
本文讨论了基于自组织特征映射网络聚类算法的基本原理，并指出了算法的缺陷。
To facilitate clustering analysis and visualization of data, the Emergent Self-Organizing Feature Maps (ESOM) and a boundless U-matrix are needed.
本文通过利用涌现自组织特征映射神经网络对数据进行聚类分析，并通过无边界u矩阵实现可视化功能。
This paper introduces a newly generalized and dynamic structure for the similarity retrieval of high dimensional feature vectors called the recursive clustering index tree.
文章提出了一种新的适用于高维特征矢量相似检索动态聚类索引树结构。
This paper's main works is that: learning algorithm studies of support vector machine, mathematical model and application about feature selection, convergence analysis of clustering algorithm.
本文主要致力于支持向量机、近似支持向量机的学习算法研究，特征提取的数学模型与算法的改进及其应用，聚类分析算法的收敛性证明。
A weighted method of customer's time series is proposed and statistical features of time series are adopted for customer clustering, which make each group of customers have similar sequence feature.
提出了客户时间序列的加权处理方法，并应用客户时间序列的统计特征作为聚类特征向量，采用混合式遗传算法对客户聚类，使每一类客户具有相似的时序特征。
The concepts of high attribute dimensional information system are firstly proposed, and a new dynamic clustering method on the basis of sparse feature difference degree is presented.
针对高属性维稀疏数据聚类问题，提出高属性维稀疏信息系统概念，给出一种新的基于稀疏特征差异度的动态抽象聚类方法。
The way, which is to determine the number of clustering by the distance between the image feature vectors, could provide more accurate retrieval result in a shorter time.
而通过图像特征向量之间的距离来确定聚类个数的方法，能在较短的时间内提供较为准确的检索结果。
The rule distance function is the key feature of rule clustering.
规则距离函数是规则聚类中的重要一环。
In this paper, we propose a model-based, self organizing feature map algorithm for the clustering of variable-length sequences.
本文提出一种基于模型的、适合变长符号序列的自组织聚类算法。
This paper proposes CF-WFCM algorithm including feature weight learning algorithm and clustering algorithm.
提出CF-WFCM算法，该算法分为属性权重学习算法和聚类算法两部分。
The novel feature distinguishes relative distribution between in-phase and quadrature components and lightens the great influence caused by noise and other random factor in clustering algorithm.
将截获信号的直观几何特征（星座图）映射到变换域中，可区别不同调制内部的同相正交分量的相对关系，避免了聚类算法受噪声干扰和其他随机因素影响。
The novel feature distinguishes relative distribution between in-phase and quadrature components and lightens the great influence caused by noise and other random factor in clustering algorithm.
将截获信号的直观几何特征（星座图）映射到变换域中，可区别不同调制内部的同相正交分量的相对关系，避免了聚类算法受噪声干扰和其他随机因素影响。
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