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• W2049003905 abstract "Discretization of continuous attributes is a necessary pre-requisite in deriving association rules and discovery of knowledge from databases. The derived rules are simpler and intuitively more meaningful if only a small number of attributes are used, and each attribute is discretized into a few intervals. The present research paper explores the interrelation between discretization and reduction of attributes. A method has been developed that uses Rough Set Theory and notions of Statistics to merge the two tasks into a single seamless process named dynamic discreduction. The method is tested on benchmark data sets and the results are compared with those obtained by existing state-of-the-art techniques. A real life data on TRIP steel is also analysed using the proposed method." @default.
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• W2049003905 date "2011-07-01" @default.
• W2049003905 modified "2023-10-16" @default.
• W2049003905 title "Dynamic discreduction using Rough Sets" @default.
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• W2049003905 doi "https://doi.org/10.1016/j.asoc.2011.01.015" @default.
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