| 1. | Improved fuzzy kernal algorithm for gene expression data clustering
基因表达数据聚类中模糊核算法的改进 |
| 2. | Cluster analysis has recently become a highly active topic in data mining research field
数据聚类是数据挖掘研究领域中一个非常活跃的研究课题。 |
| 3. | It first introduces the concept of data clustering and data classification . then it discusses eleven methods of cluster analysis
首先介绍聚类和分类的概念，然后讨论了十一种数据聚类方法。 |
| 4. | Through analyzing the characteristics of nominal data , clustering algorithm of nominal data based on entropy and hierarchical method was proposed
摘要通过对标称数据的分析，提出了一种基于信息熵和层次聚类思想的标称数据聚类算法。 |
| 5. | Abstract : according to the similitude definition between data , this paper proposes an efficient multi - dimension fuzzy clusteringalgorithm by dimension reducing and sorting
文摘:本文根据数据间相似程度的定义，利用排序缩小范围，提出一种多维数据聚类的算法。 |
| 6. | A detailed comparison which involved usual clustering algorithm in data mine was given , and a comparing analysis of usual clustering algorithm including five synthetic evaluating criterion was also given
在对聚类算法进行比较分析的基础上，从聚类的本质特点出发，将计算智能中的模拟退火算法应用到数据聚类中。 |
| 7. | In the field of data mining , efforts have focused on finding methods for high performance and effective cluster analysis in large databases . real - world applications may need to perform clustering under various kinds of constraints
在数据挖掘领域中，数据聚类的研究工作主要集中在为大型数据库的有效性和实际聚类分析寻找适当方法。 |
| 8. | In this paper , we do a lot of experiments on artificial data and real world data , and make a comparison with classical data clustering methods . the experimental results prove its great advantage over others
本文中，我们将它与传统的数据聚类方法分别对模拟数据和真实数据做以实验，并加以比较，证明了该方法优于传统方法，验证了它的优良性。 |
| 9. | After researching deep into the building and combination on model based on database , the author puts forth a search algorithm of data mining by use of prototype library and a data - clustering algorithm on the basis of expanded cf - tree
本文对基于数据库的模型生成和模型组合作了较深入的研究，给出了基于原型库的数据开采搜索算法和基于扩充cf -树数据聚类算法。 |
| 10. | A large number of experiments on image retrieval together with the comparison with the conventional comatrix method show the validity and effectiveness of the method presented here . on this basis further study is made on the features of grouping by similarity and capture
在此基础上，对脉冲耦合神经网络的以相似性集群特性和捕获特性进一步研究，提出了一种新的基于脉冲耦合神经网络的数据聚类方法。 |
