Improving the cAnt-MinerPB Classification Algorithm
نویسندگان
چکیده
Ant Colony Optimisation (ACO) has been successfully applied to the classification task of data mining in the form of Ant-Miner. A new extension of Ant-Miner, called cAnt-MinerPB, uses the ACO procedure in a different fashion. The main difference is that the search in cAnt-MinerPB is optimised to find the best list of rules, whereas in AntMiner the search is optimised to find the best individual rule at each step of the sequential covering, producing a list of best rules. We aim to improve cAnt-MinerPB in two ways, firstly by dynamically finding the rule quality function which is used while the rules are being pruned, and secondly improving the rule-list quality function which is used to guide the search. We have found that changing the rule quality function has little effect on the overall performance, but that by improving the rule-list quality function we can positively affect the discovered lists of rules.
منابع مشابه
cAnt-MinerPB Classification Algorithm
Ant colony optimization (ACO) algorithms for classification in general employ a sequential covering strategy to create a list of classification rules. A key component in this strategy is the selection of the rule quality function, since the algorithm aims at creating one rule at a time using an ACObased procedure to search the best rule. Recently, an improved strategy has been proposed in the c...
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