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Data Mining for Fuzzy Decision Systems in Banking

Nikhat Khan, Dr.Fozia Z. Khan

Abstract


Fuzzy Logic is a type of logic that is differentiated from its counterpart; Boolean Logic by the fact that it can contain "vague" information. It can contain variables between the tradition 1 and 0, such as high, medium or low. A Fuzzy decision system is a decision system based on Fuzzy Logic. Data Mining is a process that attempts to analyze data from large databases. Some popular methods for data mining include association rule learning that is used to discover interesting relationship between variables, classification, clustering, decision trees and neural networks. This study emphasizes on association rule learning, a popular data mining method for fuzzy decision systems in banking sector. A fuzzy decision system is to be built on the basis of information found from model data through the method of knowledge discovery in Databases. The Target will be identified first, followed by Data Mining and the analyzed information shall be put to use in a fuzzy decision system. The final steps will be application and evaluation. The data will be applied into the marketing wing of a Banking company, to promote a term deposit, and the method used will be direct marketing in the form of Phone Calls.

Keywords


Association Rule Learning, Customer Analytics, Data Mining, Fuzzy Decision System

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