The Data analysis inspires many applications in the field of Computing. It may be a phase either in design or on-line operation. The procedures of Data analysis are dichotomized as exploratory and confirmatory. Irrespective of these two types, the primary component for both procedures is grouping or classification. It can be done based on either (i) goodness-of-fit to a postulated model or (ii) natural groupings (clustering) revealed through analysis. Clustering is a process of partitioning a set of data or objects into a set of meaningful sub-classes, called clusters based on similarity. Obliviously, clustering has its own impact in solving complex real world problems. This paper addresses the impact of clustering algorithms for one such problem i.e. for the prediction of absenteeism at work place. The proposed method will draw predictions about absenteeism at work place by decision cluster based rule generation.

Computing, Data Analysis, Clustering, Classification

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