A Shapelet Transform for Multivariate Time Series Classification
University of East Anglia（东英吉利大学）
英文摘要：
Shapelets are phase independent subsequences designed for time series classification. We propose three adaptations to the Shapelet Transform (ST) to capture multivariate features in multivariate time series classification. We create a unified set of data to benchmark our work on, and compare with three other algorithms. We demonstrate that multivariate shapelets are not significantly worse than other state-of-the-art algorithms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
