I want know about an algorithm or formula to find the asymptote from coordinates obtained from Machine Learning. Like the ML will always give points precise & closer to the Asymptote if I ran it, but won't ever reach the asymptote value. The normal methods are only created for humans like: limit tends to zero -> 0 and by graphing but there is not an algorithms way for computers which can compute an asymptote. If anybody knows about this can give me a direction on this topic.
Stéphane Breton
Hello Tejas,
Please have a look at differential geometry in statistical theory to help you in addressing your issue :
- Barndorff-Nielsen et al., " The Role of Differential Geometry in Statistical Theory ", 1986 - https://www.nuffield.ox.ac.uk/users/cox/cox168.pdf
Regards
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Shankar Lal
Conference Paper Classification Based on Parametric Partitioning of Solution Space.
The approach creates a hyper cube around test point effectively.
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