In this paper, we propose a new clustering algorithm based on cluster validity indices, which obviates the needs for cluster parameters.
本文提出了一种新的基于有效性指数的聚类算法，无需提供聚类的参数。
The optimal feature number is decided automatically by the introduced cluster validity function.
该算法通过引入聚类有效性函数，实现了最优特征数目的自动确定。
The problems relating to cluster include data preprocessing, similarity measure and cluster validity.
与聚类相关的问题的有数据预处理、相似性度量、聚类有效性等。
One model is fuzzy cluster analysis of gene expression data based on a cluster validity measure named Xie-Beni index.
一种模型是基于有效性测度谢白尼指数的基因表达数据的模糊聚类分析。
For many clustering algorithms, it is very important to determine an appropriate number of clusters, which is called cluster validity problem.
对于许多聚类算法，决定合适的聚类数目至关重要，这称为聚类有效性问题。
A cluster validity function-based method is proposed for solving the problem of clustering for area geographical entities when the number of cluster is unknown.
为解决聚类数未知条件下面状地理实体的聚类问题，文中提出了一种基于聚类有效性函数的聚类方法。
Sometimes, the definition of similarity in the clustering algorithm is not consistent with that in the cluster validity index, so that the value of index is useless in this case.
聚类算法与聚类评价指标所采取的相似性定义往往并不一致，这就导致了在某种意义下聚类评价指标的无用性。
Cluster validity index is used to scale the validity of clustering, and determine the number of clusters.
聚类有效性指标既可用来评价聚类结果的有效性，也可以用来确定最佳聚类数。
Two factors are considered in cluster-validity criterion to enhance the robustness of algorithm and the validity of clustering, one is fuzzy membership and the other is geometric property.
新的目标准则函数考虑了数据集样本的模糊隶属关系和样本几何分布两个方面的因素，使算法的鲁棒性和分类的正确性大大加强。
Two factors are considered in cluster-validity criterion to enhance the robustness of algorithm and the validity of clustering, one is fuzzy membership and the other is geometric property.
新的目标准则函数考虑了数据集样本的模糊隶属关系和样本几何分布两个方面的因素，使算法的鲁棒性和分类的正确性大大加强。
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