Preprocessing and generation of association rules for Automated Blood Cell Counter data in haematology

The raw data from an Automated Blood Cell Counter is transformed in to a Preprocessed and Flattened data using the preprocessing phases of the Knowledge Discovery in Databases and the transformed data is used to create meaningful associations between the attributes of the database in this paper. Various Association Rules are generated using general algorithm and apriori algorithm. The apriori algorithm is found to be efficient than the general algorithm. Twelve thousand records are taken from a clinical laboratory for processing.