A Granular Ranking Algorithm for Mining Market Values

This paper proposes a granular ranking algorithm for mining market values, gives the framework of algorithm and the concrete algorithm steps. The core of new algorithm is the construction of granular ranking function r_G (x), which guides instances in the testing dataset finish ranking. The ranked result has a strong readability. The new algorithm improves the computation efficiency further relative to existing algorithms, e.g. the market value function. The experiment result shows that the computation accuracy of granular ranking algorithm approaches to the market value function. Meanwhile, incremental granular ranking algorithm also is discussed in the paper.