Accelerating improvement of fuzzy rules induction with artificial immune systems

The paper introduces an algorithmic improvement to IFRAIS, an existing Artificial Immune System method for fuzzy rule mining. The improvement presented consists of using rule buffering during the computation of fitness of rules. This is achieved using a hash table. The improved method has been tested against two different fitness functions and various data sets. Experimental results show improvements in computing times in the order of 3 to 10 times maintaining same levels of accuracy.

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