Clustering is the process of grouping similar data into a set of clusters. Cluster analysis is
one of the major data analysis techniques and k-means one of the most popular partitioning …

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 …

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 …

Partition-based clustering technique is one of several clustering techniques that attempt to
directly decompose the dataset into a set of disjoint clusters. K-means algorithm …

The most widely used algorithm in the cluster partitioning method is the K-Means algorithm.
Historically K-Means is still the best grouping algorithm among other grouping algorithms …

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 …

The k-means clustering algorithm is one of the most commonly used algorithms for
clustering analysis. The traditional k-means algorithm is, however, inefficient while working …

Clustering is a technique for dividing a set of similar objects into same groups and dissimilar
objects into different groups. Among different clustering algorithms, the K-means algorithm is …

K-means is an effective clustering technique used to separate similar data into groups based
on initial centroids of clusters. In this paper, Normalization based K-means clustering …

K-means clustering algorithm is one of the most widely used clustering algorithms and has
been applied in many fields of science and technology. A major problem of the original k …