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Rules Extraction using Data Mining in Historical Data

Rules Extraction using Data Mining in Historical Data
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Author(s): Manish Kumar (IIIT, Allahabad, INDIA)and Shashank Srivastava (IIIT, Allahabad, India)
Copyright: 2016
Pages: 17
Source title: Business Intelligence: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-9562-7.ch014

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Abstract

Rules are the smallest building blocks of data mining that produce the evidence for expected outcomes. Many organizations like weather forecasting, production and sales, satellite communications, banks, etc. have adopted this mode of technological understanding not for the enhanced productivity but to attain stability by analyzing past records and preparing a rule-based strategy for the future. Rules may be extracted in different ways depending on the requirements and the dataset from that has to be extracted. This chapter covers various methodologies for extracting such rules. It presents the impact of rule extraction for the predictive analysis in decision making.

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