Cluster validity evaluation is a hot issue in clustering algorithm research. Aiming at
determining the optimal number of clusters in cluster validity evaluation, this paper proposes …

The evaluation on clustering results is an important component of clustering analysis, which
can be conducted by the cluster validity index. However, the performances of most existing …

Different clustering algorithms achieve different results with certain data sets because most
clustering algorithms are sensitive to the input parameters and the structure of data sets. The …

The true cluster number of the dataset in practical applications is rarely known in advance.
Therefore, it is necessary to use a cluster validity index to evaluate the clustering results and …

There are various cluster validity indices used for evaluating clustering results. One of the
main objectives of using these indices is to seek the optimal unknown number of clusters …

Data Clustering is a technique of finding similar characteristics among the data set which are
always hidden in nature and grouping them into groups, called as clusters. Different …

With the widely used of data mining and cluster analysis, cluster validation is attracting
increasing attention. In this paper, the concept and development of cluster validation are …

It is crucial to evaluate the clustering quality in cluster analysis. In this paper, a new internal
cluster validity index based on the cluster centre and the nearest neighbour cluster is …

Many validity indices have been proposed for quantitatively assessing the performance of
clustering algorithms. One limitation of existing indices is their lack of generalizability, due to …

Validating a given clustering result is a very challenging task in real world. So for this
purpose, several cluster validity indices have been developed in the literature. Cluster …