In financial time series prediction and data mining research, Piecewise Linear Representation (PLR) is generally used for time series data preprocessing, but the PLR algorithm uses a single fitting error as the threshold, and the segmentation effect is not ideal, and the versatility, time complexity and other shortcomings of PLR need to be improved. This paper proposes a financial time series region segmentation method, which is superior to the traditional piecewise linear method in both qualitative and quantitative.
