Association ACDT as a tool for discovering the financial data rules

We present a novel approach based on the original idea of the Ant Colony Decision Tree (ACDT) algorithm used in the problem of building the decision trees. One of the crucial limitations of the canonical ACDT algorithm was its link to strict decision rules. In this paper we transform the algorithm in such way, that it is capable to manage complex association rules. Research is conducted on the various sets of financial data closely related with the swiss frank currency. Evaluation of results was possible on the basis of accuracy measure as well as the proposed fuzzy accuracy. These preliminary studies show, that the proposed algorithm is capable to maintain its effectiveness even in the problems with large number of attribute values.