Abstract: The traditional three-wany decision rough set model needs to set up appropriate threshold. It requires the user of the model to have the relevant professional knowledge and experience, which hinders the application of the model in practice. To solve this problem, the artificial fish swarm algorithm is proposed to generate the threshold automatically, without requiring priori knowledge. Taking the conditional probability of sample as the target, using the artificial fish swarm algorithm, it can effectively learn from the data to the threshold required by the three-wany decision rough set model. It can make the risk loss minimum. The experimental result in part of UCI data sets shows that the algorithm run much faster than the adaptive learning parameters algorithm, and a three-decision-making classifier was built by using the threshold and this classifier can also make classifier better.
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Key words: three-way decision-theoretic rough set model, artificial fish swarm algorithm, thresholds, cost function