An effective Fuzzy Healthy Association Rule Mining Algorithm (FHARM)
نویسندگان
چکیده
In this paper we propose an effective and efficient new Fuzzy Healthy Association Rule Mining Algorithm (FHARM) that produces more interesting and quality rules by introducing new quality measures. In this approach, edible attributes are filtered from transactional input data by projections and are then converted to Required Daily Allowance (RDA) numeric values. The averaged RDA database is then converted to a fuzzy database that contains normalized fuzzy attributes comprising different fuzzy sets. Analysis of nutritional information is then performed from the converted normalized fuzzy transactional database. The paper presents various performance tests and interestingness measures to demonstrate the effectiveness of the approach and proposes further work on evaluating our approach with other generic fuzzy association rule algorithms.
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