Data mining is finding hidden rules in given dataset using non-traditional methods. The objective is to discover some useful tendency or patterns from the given collection of data. We had mined the rules representing the effect of cognitive style, subjective emotion, and physiological phenomena on the accuracy of subjects' judgmental time-series forecasting. Then we have tried to find out any consistent tendencies in the frequent rules. Subjects in Analytic-style show more accurate forecasting. Subjects in relaxed mode show more accurate forecasting. And Subjects’ left EEG and beta rhythm seem to have a significant effect on their forecasting accuracy. But additional data mining to the other effects should be made.
Song, Byoungho; Park, Hung Kook; and Yoo, Hyeon Joon, "A Data Mining for the Effect of Cognitive Style, Subjective Emotion, and Physiological Phenomena on the Accuracy of Judgmental Time-Series Forecasting" (2000). AMCIS 2000 Proceedings. 34.