Cluster Analysis is one of the most important data mining techniques which help the
researchers to analyze the data and categorize the attributes of data into various groups. K …

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 method is one of the main analytical methods in data mining, the method
of clustering algorithm will influence the clustering results directly. This paper discusses the …

The K-Means clustering algorithm is proposed by Mac Queen in 1967 which is a partition-
based cluster analysis method. It is used widely in cluster analysis for that the K-means …

This paper introduces an optimized version of the standard K-Means algorithm. The
optimization refers to the running time and it comes from the observation that after a certain …

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 …

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 …

Representing the data by smaller amount of clusters necessarily loses certain fine details,
but achieves simplification. The most commonly used efficient clustering technique is k …