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Changepoint detection may be senstive to extreme outliers #998
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Alternatively, should be fixed by #906 |
@abhidg Can we have a look at this please? The method I had before here (using R) worked fine in this regard. |
Not sure there's any point picking off small issues on the functional testing @ben18785 ! We need someone to sit down for it in earnest for a few days and work out what to do + how best to do it. See e.g. the other tickets open on "functional testing" https://github.com/pints-team/pints/issues?q=is%3Aissue+is%3Aopen+label%3Afunctional-testing |
Yep, but think one of the main reason it's failing is due to the way in
which we are doing this changepoint detection. I did have a method in R
that seemed to work ok
…On Sat, Mar 21, 2020 at 4:12 PM Michael Clerx ***@***.***> wrote:
Not sure there's any point picking off small issues on the functional
testing @ben18785 <https://github.com/ben18785> ! We need someone to sit
down for it in earnest for a few days and work out what to do + how best to
do it. See e.g. the other tickets open on "functional testing"
https://www.instagram.com/p/B9-HYxFD4sh/
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Have you tested it on this specific data set? The code we have now works well on lots of cases, but this ticket was about a situation where it didn't give the answer I expected, so thought it was worth debugging (at the time). The main reason it's "not working" at the moment is that
So the whole thing needs thinking out |
I still think the whole changepoint thing is a really great idea btw, and possibly novel for software engineering? Would be a paper if we do it right I'll bet. Just requires some proper thinking which isn't going to come from me for the next few months at least! |
(having said that I'm now thinking about it quite a lot...) |
https://www.cs.ox.ac.uk/projects/PINTS/functional-testing/#mcmc-banana-populationmcmc-1
It works really well on other cases, but here I think I can see a change that isn't picked up. Perhaps because a while earlier there was a KL-divergence of 1e15??
Todo:
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