… data, that is, data mining clustering algorithms. Here we have studied and made a comparative
analysis of four classic clustering algorithms namely K-means, BIRCH, DBSCAN, STING. …

… This paper compared all these clustering algorithms according to the many factors. After
comparison of these clustering algorithms I describe that which clustering algorithms should be …

… However the use of these algorithms with educational dataset is … clustering algorithms as
applied in Educational Data Mining context. Index Terms―Clustering, educational data mining (…

… clustering results directly. This paper discusses the various types of algorithms like k-means
clustering algorithms, … algorithms. In each type we can calculate the distance between each …

… operation of clustering K-means algorithm. The results show that in the K-means clustering
algorithm, we must first determine an initial value to be divided, and then use the algorithm to …

… overview and comparison of these different clustering algorithms and methods. … algorithm
we use the actual object to represent the cluster, using one representative object per cluster…

… of data mining algorithms in a very limited space. In this chapter, we concentrate on clustering
algorithms. This … and gives a quite accurate image of the challenges posed by data mining. …

… , density-based algorithms and grid-based algorithms. This paper focuses on a keen study …
different clustering algorithms in data mining. A brief overview of various clustering algorithms …

… in the data mining field, and by virtue of the well-established … clustering algorithms on static
data. Nevertheless, when analyzing data, it is important to take into account whether the data …

… data mining concept and some of the data mining algorithms. It gives the general overiew or
background about data mining and the algorithms … known to the clustering algorithm. This is …