Local search methods can quickly find good quality solutions in cases where systematic search methods might take a large amount of time. Moreover, in the context of pattern set mining, exhaustive search methods are not applicable due to the large search space they have to explore. In this paper, we propose the application of stochastic local search to solve the pattern set mining. Specifically, to the task of concept learning. We applied a number of local search algorithms on a standard benchmark instances for pattern set mining and the results show the potentials for further exploration.
In a recent work, Hossain et al. REF explored the use of genetic algorithms and other stochastic local search algorithms to solve the concept learning task using small datasets.
Stochastic local search for pattern set mining
The 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2014)
The 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2014)
Computer Science