A Review of Data Clustering Approaches

Fast retrieval of the relevant information from the databases has always been a significant issue. Different techniques have been developed for this purpose; one of them is data clustering. Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups (clusters). The clustering problem has always been a focus of many researchers in many fields and disciplines and has a broad attraction and usefulness as one of the steps in exploratory data analysis. Many problems in business, science, industry, and medicine can be treated as clustering problems. Some of the examples include bankruptcy prediction, credit scoring, medical diagnosis, quality control, handwritten character recognition, image processing and speech recognition.

Provided by: International Journal of Engineering and Innovative Technology (IJEIT) Topic: Data Management Date Added: Apr 2012 Format: PDF

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