An Empirical Evaluation of Density-Based Clustering Techniques

Provided by: International Journal of Soft Computing and Engineering (IJSCE)
Topic: Data Management
Format: PDF
Emergence of modern techniques for scientific data collection has resulted in large scale accumulation of data pertaining to diverse fields. Conventional database querying methods are inadequate to extract useful information from huge data banks. Cluster analysis is one of the major data analysis methods. It is the art of detecting groups of similar objects in large data sets without having specified groups by means of explicit features. The problem of detecting clusters of points is challenging when the clusters are of different size, density and shape.

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