Abstract
This paper applies the preprocessing phases of the Knowledge Discovery in Databases to the automated blood cell counter data and creates discrete ranges of blood cell counter data that can be used in grouping data using classification, clustering and association rule generation. The functions of an automated blood cell counter from a clinical pathology laboratory and the phases in Knowledge Discovery in Databases are explained briefly. Twelve thousand records are taken from a clinical laboratory for processing. The preprocessing steps of the KDD process are applied on the blood cell counter data. This paper applies the Chi Merge algorithm on the blood cell counter data and generates discretized data representing ranges of values for the data.
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Minnie, D., Srinivasan, S. (2013). Preprocessing of Automated Blood Cell Counter Data and Discretization of Data Using Chi Merge Algorithm in Clinical Pathology. In: Meghanathan, N., Nagamalai, D., Chaki, N. (eds) Advances in Computing and Information Technology. Advances in Intelligent Systems and Computing, vol 178. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31600-5_50
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DOI: https://doi.org/10.1007/978-3-642-31600-5_50
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