Clustering is one of the main task in datamining. It is useful to group and cluster the data.
There are a few ways to cluster the data such as partitional-based, hierarchical-based and …

Several algorithms are applied in the literature of clustering such as K-means, Fuzzy C-
Means, and Single Linkage, etc. K-means Algorithm is the most commonly used because of …

The most widely used algorithm in the cluster partitioning method is the K-Means algorithm,
K-Means is an iteration algorithm with the user determining the number of clusters that need …

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 …

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 …

Clustering is a method needed to group data or objects based on the required level between
data, K-means is one of the clustering methods used that can be used easily in its …

K-Means is a simple clustering algorithm that has the ability to throw large amounts of data,
partition datasets into several clusters k. The algorithm is quite easy to implement and run …

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 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 …

K-means algorithm is a very popular clustering algorithm which is famous for its simplicity.
Distance measure plays a very important rule on the performance of this algorithm. We have …