Clustering Assessment Tendency for Big Data Analytics: Extract Useful Knowledge

Özet

The clustering method is one of the important methods that can be used to analyze the big volume of data that should be grouped accordingly as much as possible. Depending on the characteristics of the data available today and to deal with big data challenges, several clustering methods have been developed. But, in many situations, we cannot know a priori the number of clusters in the data set. This refers to an important problem in cluster analysis or determining the numbers of clusters. In this context, this paper describes some clustering methods, with special attention to the Visual Assessment Tendency (VAT) algorithm as one of the known methods. This algorithm is implemented in advanced technologies to analyze big data. More generally, VAT algorithms are important before applying clustering analysis to classify unlabelled data. Clustering analysis requires the use of visual presentations to help understand what distinguishes classes.