查询词典 clustering

Firstly, 112 symptoms of asthenia syndrome which frequency greater than or equal to 10% were clustered and recognized. Secondly, every group cases of asthenia syndrome after first stage clustering were clustered and recognized again to get corresponding sthenia syndrome. Thirdly, we searched for the distribution laws between the clustering result and the data of demography to get the distribution laws of every group characteristic symptoms corresponding asthenia syndrome, of sthenia syndrome corresponding every group asthenia syndrome.

首先根据频率大于10%的112个虚证症状进行聚类识别，再对聚类结果中每组虚证病例进行兼夹实证聚类识别，并对聚类识别结果与性别、年龄等人口学特征之间分布规律进行探索，从而得出每类虚证对应的特征症状分布规律及程度，虚证证候对应的兼夹实证分布规律，以及各类主次证候间辨证关系及发展趋势，及其与性别、年龄等人口学特征的分布规律。

In the empirical analysis part, statistical descriptions on the sample funds are made firstly, which show that the actual distribution of each sample fund"s daily net value return possesses the characteristic of leptokurtosis. So it is necessary to add student T distribution and GED to capture such leptokurtosis characteristic other than normal distribution. Secondly, ARCH test shows that there exists volatility clustering in each sample fund"s daily net value return, so GARCH related models should be used to describe such volatility clustering characteristic.

实证分析部分首先对样本基金进行统计描述，得出其收益序列均存在尖峰厚尾特征，不服从正态分布，因此有必要在下面的VaR计算中加入T分布和GED分布来捕捉这种尖峰厚尾特征；并且经ARCH检验后得出收益序列存在明显的波动聚集性的特征，因此可以选择GARCH类模型来描述这种特性，经过模型筛选，得出最适合我国开放式股票型基金的收益波动性模型为GARCH(1，1)模型。

According to the comparison of delineation management zones between improved ant colony clustering and K-means clustering, management zones delineated by the former showed the features that soil physical properties had stronger uniformity within the subzone and more significant difference between subzones.

将改进的蚁群聚类分区结果与传统的K-均值聚类进行比较，前者分区结果表现出土壤物理特性区内均一性更强、区间差异性更加显著的特点。

For this purpose, this paper presents a novel clustering algorithm for these mixed data sets by modifying the common cost function, trace of the within cluster dispersion matrix. The Genetic Algorithm is used to optimize the new cost function to obtain valid clustering result.

为此，该文提出了一种基于GA的模糊聚类新算法，通过改进聚类目标函数将数值特征与类属特征相结合，从而实现具有混合属性特征数据的聚类分析；通过引入GA算法能够快速得到全局最优解，而且不依赖于原型初始化。

This paper introduces the fundamental mind of fuzzy clustering analysis and carries on clustering analysis using the transitive closure method.

比如遥感图像上的某个样本属于某个类别或不属于某个类别是一个模糊概念[1]，这些模糊概念便产生了经典分类学解决不了的困难，模糊聚类分析就应运而生了。

Therefore, this paper fuzzy clustering method, first of all to highlight the dangers of all kinds of mining coal seams of each index measured data as samples to establish fuzzy similar matrix, find the transitive closure, re-use to do clustering, plot dendrogram.

所以本文利用模糊聚类方法，首先把矿区内各种突出危险性煤层的各指标的实测数据作为样本，建立模糊相似矩阵，求出传递闭包，再利用做聚类，画出聚类图。

Fuzzy C-means clustering model is one of the well known unsupervised clustering techniques, which has been widely used.

模糊C均值聚类是一种经典的非监督聚类模型，已成功用于很多领域。

ABSTRACT: Random amplified polymorphic DNA was used in analysing the relationship among twenty-six speices of Amanita from Mangshan, Hunan. Of 40 primers, 6 ones generated reproducible RAPD profiles, and each one produced 1-10 bands. Two primers (OPG15 and OPH04) could differentiate 26 species of Amanita by its RAPD profiles. The similarity coefficients obtained from profiles generated by six primers among Amanita were about 20-60%. A dendrogram was constructed using average linkage clustering for clustering analysis. It indicated that there were two groups in 26 species and some species with ring and membranous volva clustered a group which coincided with morphological classification.

本文对采自湖南莽山的26种鹅膏菌属真菌进行了随机扩增多态性DNA分析，40个随机引物中筛选出扩增效果较好的6个引物，每个引物能产生1～10条DNA条带，获得的RAPD谱带清晰并呈现多态性OPG15、OPH04两个引物扩增的RAPD谱带能将26种鹅膏菌完全区分开来，通过6个引物的RAPD分析获得的平均相似性系数表明种与种之间的相关系数在20―60%之间，平均链锁聚类分析可将26种鹅膏菌分为二大类，且一些具菌环和苞状菌托的种类聚在一起，与形态分类基本相吻合。

In order to overcome the weakness of clustering in the WEKA system,the paper makes secondary development under the WEKA platform to extend the clustering algorithms.

为了克服WEKA系统在聚类方面的薄弱性，在WEKA的开源环境下进行二次开发，扩充了聚类算法。

Methods such as hierarchical agglomerative clustering, k-means clustering, the self-organizing map, and model-based methods have been used.

使用了诸如层次聚合聚类方法、k-均值聚类、自组织映射，和基于模型的方法。

"Yes, now you can give yourself airs," she said, you have got what you wanted.

"对了，您现在高兴了，"她说道，这是您所期待的。

Then the LORD said to me: Rebel Israel is inwardly more just than traitorous Judah.

上主于是对我说：＂失节的以色列比失信的犹大，更显得正义。