Clustering analysis is the most significant step in data mining. This paper discusses the k-
means clustering algorithm and various distance functions used in k-means clustering …

Data clustering is a process of arranging data into groups or a technique for classifying a
mountain of information into some manageable meaningful piles. The goal of clustering is to …

K-means clustering algorithm clusters datasets according to the certain clustering number k.
However, k cannot be confirmed beforehand. A new clustering validity index was designed …

In k-means clustering algorithm, the number of centroids is equal to the number of the
clusters in which data has to be partitioned which in turn is taken as an input parameter. The …

Clustering is the process of grouping the data based on their similar properties. Meanwhile,
it is the categorization of a set of data into similar groups (clusters), and the elements in each …

K-Means clustering algorithm attracts increasing focus in recent years. A pending problem of
K-Means clustering algorithm is that the performance is affected by the original cluster …

Clustering analysis plays an important role in scientific research and commercial
application. K-means algorithm is a widely used partition method in clustering. As the …

This paper presents a comprehensive review of existing techniques of k-means clustering
algorithms made at various times. The kmeans algorithm is aimed at partitioning objects or …

Study of this paper describes the behavior of K-means algorithm. Through this paper we
have try to overcome the limitations of K-means algorithm by proposed algorithm. Basically …