sktime is an open source, Python based, sklearn compatible toolkit for time series analysis developed by researchers at the University of East Anglia, University College London and the Alan Turing Institute. A key initial goal for sktime was to provide time series classification functionality equivalent to that available in a related java package, tsml. We describe the implementation of six such classifiers in sktime and compare them to their tsml equivalents. We demonstrate correctness through equivalence of accuracy on a range of standard test problems and compare the build time of the different implementations. We find that there is significant difference in accuracy on only one of the six algorithms, and this difference was to be expected. We found a much wider range of difference in efficiency. Again, this was not unexpected, but it does highlight ways both toolkits could be improved.
翻译:Sktime是一个开放源码,以Python为基础,klearn兼容的工具包,供东安格利亚大学、伦敦大学学院和Alan Turing研究所研究人员开发的时间序列分析使用。对于sktime来说,一个关键的初始目标是提供相当于相关java软件包(tsml)中可用的时间序列分类功能。我们描述六个这种分类器在时间上的使用情况,并将其与等同物进行比较。我们通过对一系列标准测试问题的准确性进行等同来显示正确性,并比较不同执行过程的构建时间。我们发现,在六种算法中,只有一种算法的准确性差异很大,而且这种差异是可以预测的。我们发现,效率差异的范围要大得多。我们发现,这并非出人意料,但确实突出了两种工具都可以改进的方法。