Research on event prediction in time-series data
Xiangbin Yan, Tao Lu, Yijun Li, Guangbin Cui · 2005
Event prediction in time series is an important problem with many real world applications. Existing statistical and machine learning methods are not suitable for the problem. This paper describes a neural network system that predicts events by identifying features extracted from time-series data. A new feature extraction method is proposed and a corresponding clustering method is given. The method is applied to real time series and the resulting generalization performance of the trained feed-forward neural network predictors is analyzed. It shows that the method is effective in event prediction.