The choice of a proper similarity/dissimilarity measure is very important in cluster analysis for
revealing the natural grouping in a given dataset. Choosing the most appropriate measure …

This paper introduces k′-means algorithm that performs correct clustering without pre-
assigning the exact number of clusters. This is achieved by minimizing a suggested cost …

We present the global k-means algorithm which is an incremental approach to clustering
that dynamically adds one cluster center at a time through a deterministic global search …

K-means clustering is a popular clustering algorithm based on the partition of data.
However, K-means clustering algorithm suffers from some shortcomings, such as its …

Clustering technique is used to put similar data items in a same group. K-mean clustering is
a common approach, which is based on initial centroids selected randomly. This paper …

Data mining is the process of finding structure of data from large data sets. With this process,
the decision makers can make a particular decision for further development of the real-world …