Application of association rules in stock analysis
Song Su · Jisuanji gongcheng · 2005
The Apriori arithmetic adopted the changing support and confidence was applied to mine one-dimension and multi-dimension stock information. It was familiar to take the stocks' codes as the results of data processing, but the stocks' transaction time was selected as the results of data processing aiming at the convenience and celerity during the concrete mining. It took the tier of transaction time as the direct object of arithmetic of data mining and took the transaction time as the indirect object of arithmetic of data mining. After such data processing, it was effective not only to mine the interesting rules, but also to avoid the trouble that the results of the data processing need to be reprocessed during the mining of multi-dimension information. The mining results have been proved to be right by the validation of the representational rules.