Experimental study of Data clustering using k-Means and modified algorithms

Experimental study of Data clustering using k - Means and modified algorithms

The kMeans clustering algorithm is an old algorithm that has been intensely researched owing to its ease and simplicity of implementation. Clustering algorithm has a broad attraction and usefulness in exploratory data analysis. This paper presents results of the experimental study of different approaches to kMeans clustering, thereby comparing results on different datasets using Original k-Mean...

A Hybrid Data Clustering Algorithm Using Modified Krill Herd Algorithm and K-MEANS

Data clustering is the process of partitioning a set of data objects into meaning clusters or groups. Due to the vast usage of clustering algorithms in many fields, a lot of research is still going on to find the best and efficient clustering algorithm. K-means is simple and easy to implement, but it suffers from initialization of cluster center and hence trapped in local optimum. In this paper...

Simultaneous Pattern and Data Clustering Using Modified K-Means Algorithm

In data mining and knowledge discovery, for finding the significant correlation among events Pattern discovery (PD) is used. PD typically produces an overwhelming number of patterns. Since there are too many patterns, it is difficult to use them to further explore or analyze the data. To address the problems in Pattern Discovery, a new method that simultaneously clusters the discovered patterns...

Persistent K-Means: Stable Data Clustering Algorithm Based on K-Means Algorithm

Identifying clusters or clustering is an important aspect of data analysis. It is the task of grouping a set of objects in such a way those objects in the same group/cluster are more similar in some sense or another. It is a main task of exploratory data mining, and a common technique for statistical data analysis This paper proposed an improved version of K-Means algorithm, namely Persistent K...

Segmentation of Photospheric Solar Images by Using c-Means,k-Means, and FCM Algorithms