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I suppose it's because of the discrepancies between a local maximum point of the interpolant and the corresponding hill in the database.
I've come up with an idea to solve such discrepancy: find some local optimizer that has a small learning rate, and for each hill in the database, use its location as the starting point of the local optimizer. We'll end up somewhere near our starting point but with a larger height (we must check the proximity), and then we update the database with this point.
Or maybe there's a fixed discrepancy for all the hills? I.e. we simply need to move all the locations in the database by a fixed amount to match the hills with the local maxima. I haven't worked on this yet so I'm not sure.
Hi Eric, Yeah the hills database doesn't agree with our data set entirely, and that's fine.
What worries me is why the red line above isn't exactly on the maximum of the blue line. Both are from our interpolant, so the hills db doesn't come into play here
Oh, then I suppose that might have something to do with the optimizer, which might stop iterating only near the highest point, potentially because of its "minimum step"?
Why do we see these some times?
I.E. did the optimiser not find the optimum, is it a plotting issue, or something else?
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