Applying rough sets in the data mining of the case study on financial markets

Rough Set Theory was presented by Zdzislaw Pawlak in ۱۹۸۱. In this hypothesis the data set that are non-definite and incompatible are converted to reduced and valid sets for decision making. In this theory by considering the data set in two sets consisting of under approximation and over approximation, the desired subsets are provided for us to process and to analyze them. Applying rough sets in financial markets, in economics etc. In which a large amount of data will be effective so that one can make decisions has caused the data sets to be reduced and changed into the desired set in order to show the capability of this theory for practical uses. In this article we intend to introduce this theory and its operators. At first a history and some literature on what is done about Rough Set Theory is presented and then its application will be discussed in classifying and we will clarify the point with some examples for better understanding of this theory.

کلیدواژه ها:

Rough Set Theory ، soft computing ، information systems ، data processing