聚类结果与形态分类结果不完全一致。
The results of cluster analysis were consistent with morphological classification by and large.
最后给出文本聚类结果描述的评价方法。
The evaluation methods of DCD are also described in this paper.
聚类结果可按不同的要求确定类型的多寡。
The number of types in the clustering results may be determined by different requirement.
然后，引入转移矩阵来验证聚类结果的合理性；
Secondly, the thesis validates the classification result rational or not by Transformation Matrix.
合并连接紧密度高的结点，得到最后的聚类结果。
Combining the nodes which have the high joint degree, we can get the result of the clustering.
而设置不合理的聚类参数又使得聚类结果质量变低。
It will output a low quality clustering result if user set unsuitable parameters before clustering operation.
根据聚类结果，讨论了分布聚类与动物地理区划的关系。
Relationship between the distribution cladisfic and the zoogeographical projecfion was discussed based on the result of the cladisfic.
然后对数据先进行聚类，再在聚类结果中发掘频繁项目集；
The second, clustered the data, and then discovered frequent items sets in the result of clustering.
根据遗传距离进行聚类，得出聚类结果与地理分布范围相关。
The result of genetic distance was identical to geographic distribution.
实验表明，该算法能够生成质量较高而且波动性较小的聚类结果。
The experimental result shows that the K-means with the proposed technique can produce cluster results with high purity as well as good stableness.
目前采用的聚类结果可视化方法多为统计学方法，如饼图、柱状图等。
The current clustering results visualization methods mostly statistical methods, such as bars and pie.
根据聚类结果，以中心趋势和数据分布的方式给出了描述线路状态的方法。
With the results of clustering, a description way for branch state is given by the means of central tendency and data dispersion.
改进后的聚类结果既消除了采样误差，又保持了云类样本的基本特征属性。
Therefore, the improved FCM clustering results can reduce the sampling errors and retain the main attributes of cloud classification samples.
星座图聚类是表型性状的聚类，聚类结果与自交系间的血缘无必然的联系。
There were no relationship between the result of constellation graphical cluster analysis and the kin of inbred lines.
最后考虑到像素空间的区域连续性，在颜色聚类结果的基础上进行区域生长。
Finally, considering the consecution of the district of the pixel space, on the basis of the result of color clustering, the region-growing is wanted to be processing.
归一化排除了一些干扰，使特征更加明显，野生和栽培甘草聚类结果非常理想。
Normalization reduces disturbance and makes character obvious so that clustering result of wild and planting liquorices is ideal.
聚类集成中的关键问题是如何根据不同的聚类器组合为最终的更好的聚类结果。
A critical problem in cluster ensemble is how to combine multiple clusters to yield a superior result.
为了定量分析聚类算法的聚类结果，提出了基于引力概念的聚类质量评估算法。
A clustering result evaluating algorithm is presented in a gravitational way, where all the data points in the data space are regarded as the particles assigned with unit mass.
实现了随机点图、顺序点图、电子云图、条形图、饼图五种聚类结果可视化方法。
Several visualization methods of displaying clustering results were realized, it includes the chart of random points, order points, electron cloud, bars and pie.
提出以加权距离和系统相似度量方法为基础进行聚类分析，提高聚类结果的有效性。
Cluster Analysis is argued to process based on Weighted Distance Coefficient and System Similarity methods to enhance the validity of the clustering result.
结论根据聚类结果，玫瑰品种类型的划分应首先考虑亲本来源，再按株型、花型划分。
ConclusionBased on the result of cluster analysis, the species origin should be considered firstly in the classification of Rosa rugosa, then the plant type and the flower type.
提出了在人才认知系统中使用回归分析的方法，对第四章的聚类结果进行了回归分析。
It points out the method of Regression Analysis used in talents cognition system and Regression Analysis has been made in Clustering result of the fourth chapter.
均值算法的聚类个数k需指定，聚类结果与数据输入顺序相关，而且易受孤立点影响。
K-means algorithm has some deficiencies. The number K must be pointed and its effectiveness liable to be effected by isolated data and the input sequence of data.
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。
MFCC USES intermediate clustering results in one type of feature space to help the selection in other types of feature Spaces.
针对上述问题，本文提出三种聚类结果的可视化方法：随机点图、顺序点图、电子云图。
In response to these problems, we present three visualization methods of displaying clustering results, it includes the chart of random points, order points, electron cloud.
依照所得的两种综合得分进行风险聚类； 并以聚类结果构建企业财务风险标准模型库。
Two comprehensive scores obtained were categorized into risk, the result of which was used to build standard model base of financial risk of enterprise.
数值实验结果也说明FBACN算法的结果与与其对应的FCM算法的聚类结果并不相同。
While from the result of the experiment do in this paper, find that the FBACN algorithm is not equal to FCM.
算法提出了一种简洁快速的初始聚类中心的选取规则，从而使获得的聚类结果为全局最优。
The new algorithm can obtain global optimal solutions through a new simple and efficient select rule of the initial cluster centers.
算法提出了一种简洁快速的初始聚类中心的选取规则，从而使获得的聚类结果为全局最优。
The new algorithm can obtain global optimal solutions through a new simple and efficient select rule of the initial cluster centers.
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