The training time of Kriging model and GEKPLS

[plantom007]

@relf
Hi,I'm sorry to bother you.I trained the function with kriging , KPLS and GEKPLS respectively. I used 100 training points, just like the article said. But the GEKPLS is the slowest, and the KPLS is not as fast as the article said. To my confusion, the performance of the kriging model is not as bad as I expected.When training a 20 dimensional sphere function with 500 points. It took 186s for kriging and 177s for KPLS and 175s for GEKPLS. Does the ordinary kriging of the smt toolbox modify something?

[relf]

Does the ordinary kriging of the smt toolbox modify something?

Hi. Sorry, I am not sure to understand your question. If you try with higher dimensional problems you should see kriging performance degradation wrt KPLS performance.

Regarding the reproduction of the results of the KPLS article, as you are aware, we definitely have a problem (cf. #337, btw I fixed the link to the article).

[plantom007]

smt工具箱的普通克里金法是否会修改一些东西？

你好。 对不起，我不确定你的问题。 如果您尝试处理更高维度的问题，您应该会看到 KPLS 性能的克里金性能下降。

关于 KPLS 文章结果的再现，如您所知，我们肯定有问题（参见 #337 ，顺便说一句，我修复了文章的链接）。

Thank you very much!I probably found the problem.I regard the number of n_comp and the dimension of function as same value.This causes run slow.