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 …

Clustering Performance is based iterative and analysis is a descriptive task that seeks to
identify homogeneous groups of objects based on the values of the methodology is search …

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 …

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 …

Abstract k-mean [1] is one of the most important algorithm for Clustering. Major problem of
using k-mean type algorithms in Data mining is selection of variables (attributes). k …

Data mining has been defined as" The nontrivial extraction of implicit, previously unknown,
and potentially useful information from data". Clustering is the automated search for group of …

Clustering is the popular unsupervised learning technique of data mining which divide the
data into groups having similar objects and used in various application areas. k-Means is …

The k-Means clustering algorithm is an old algorithm that has been intensely researched
owing to its ease and simplicity of implementation. Clustering algorithm has a broad …

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 …

Clustering is a process of partitioning a set of data (or objects) into a set of meaningful sub-
classes, called clusters, help users understand the natural grouping or structure in adata set …