Unsupervised learning is the process to partition the given data set into number of clusters
where similar data objects belongs same cluster and dissimilar data objects belongs to …

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 …

In this paper, we describe an essential problem in data clustering and present some
solutions for it. We investigated using distance measures other than Euclidean type for …

This paper presents a data clustering approach using modified K-Means algorithm based on
the improvement of the sensitivity of initial center (seed point) of clusters. This algorithm …

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 …

The cluster analysis deals with the problems of organization of a collection of data objects
into clusters based on similarity. It is also known as the unsupervised classification of objects …

In statistic and data mining, k-means is well known for its efficiency in clustering large data
sets. The aim is to group data points into clusters such that similar items are lumped together …

Clustering technique in data mining has received a significant amount of attention from
machine learning community in the last few years and become one of the fundamental …

The set of objects having same characteristics are organized in groups and clusters of these
objects reformed known as Data Clustering. It is an unsupervised learning technique for …

Cluster analysis is one of the prominent techniques in the field of data mining and k-means
is one of the most well known popular and partitioned based clustering algorithms. K-means …