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KBS
2006

Predictive and comprehensible rule discovery using a multi-objective genetic algorithm

13 years 10 months ago
Predictive and comprehensible rule discovery using a multi-objective genetic algorithm
We present a multi-objective genetic algorithm for mining highly predictive and comprehensible classification rules from large databases. We emphasize predictive accuracy and comprehensibility of the rules. However, accuracy and comprehensibility of the rules often conflict with each other. This makes it an optimization problem that is very difficult to solve efficiently. We have proposed a multi-objective evolutionary algorithm called improved niched Pareto genetic algorithm (INPGA) for this purpose. We have compared the rule generation by INPGA with that by simple genetic algorithm (SGA) and basic niched Pareto genetic algorithm (NPGA). The experimental result confirms that our rule generation has a clear edge over SGA and NPGA.
Satchidananda Dehuri, Rajib Mall
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2006
Where KBS
Authors Satchidananda Dehuri, Rajib Mall
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