Frequent patterns discovery and analysis granularity recognition for Shanghai Composite Index sequence
Gao Xuedong, Hailan Chen · 2016
The Shanghai Composite Index is a typical time series, and reflects the stock market variations. In this paper, a method is proposed for mining frequent patterns from the Shanghai Composite Index using the agglomerative hierarchical clustering algorithm based on DTW. For reflecting the nature of research question and reducing the computational complexity, the best time granularity is found by effective evaluation based on the clustering results.