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refine bail policy vs crime rate results #21

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akelleh opened this issue Jan 13, 2019 · 1 comment
Open

refine bail policy vs crime rate results #21

akelleh opened this issue Jan 13, 2019 · 1 comment

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@akelleh
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akelleh commented Jan 13, 2019

If the results of the simpler ticket work out, AND we want more robust results, we can do the following:

To make the analysis more robust, we probably want to take into account both the x and y errors. To do that, you need "total least squares" or "orthogonal least squares" regression. There's an implementation in scipy here, but the API is pretty low-level, which means it's harder to work with.
https://docs.scipy.org/doc/scipy/reference/odr.html

@mayank5695
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I am wondering that there are other methods to account for both x and y errors. We can also get that from scikit-learn library. We can easily use different regression models from there and also account for error. Do let me know what we should do about it?

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