Abstract:Shapelet provides a fast classification method in time series classification, but the extraction of time series Shapelet is so slow that it restricts the application of the Shapelet. In order to speed up the extraction of time series Shapelet, an improved method is proposed based on the principal component analysis. Firstly, it uses the principal component analysis (PCA) to reduce the dimension of time series data set and chooses the reduced data to represent the original data. Secondly, it can extract the most discriminatory Shapelet sequence from the reduced data. Lastly, the experimental results show that the improved method improves the speed of the extraction and ensures the accuracy of classification.