Abstract:
Pairs mining targets to mine pairs relationship between entities such
as between stocks and markets in financial data mining. It has emerged as a
kind of promising data mining applications. Due to practical complexities in the
real-world pairs mining such as mining high dimensional data and considering
user preference, it is challenging to mine pairs of interest to traders in business
situations. This paper presents fuzzy genetic algorithms to deal with these
issues. We introduce a fuzzy genetic algorithm framework to mine pairs
relationship, and propose strategies for the fuzzy aggregation and ranking of
identified pairs to generate final optimum pairs for decision making. The
proposed approaches are illustrated through mining stock pairs and stocktrading
rule pairs in stock market. The performance shows that the proposed
approach is promising for mining pairs helpful for real trading decision making.
