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I have a mulitvariate regression model that for which I'd like to see the residuals. I attempted to output the model's residuals via

model.residues_

But this has been deprecated. Any workarounds?

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    $\begingroup$ Compute them? y - model.predict(X)? $\endgroup$
    – Matthew Drury
    Jul 26, 2017 at 20:04
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    $\begingroup$ I deleted a duplicate answer of this one; but wanted to note also that model.residues_ returns RSS, not residuals. If you wanted the former, you coudl use np.linalg.norm(y - model.predict(X)) ** 2. $\endgroup$
    – Kevin
    Jul 26, 2017 at 20:06
  • $\begingroup$ @Kevin Since mine was just a comment, I think you're fine to state that as an actual answer. $\endgroup$
    – Matthew Drury
    Jul 26, 2017 at 20:07
  • $\begingroup$ There are saved in the object as ._residues so no need to recompute it again. $\endgroup$
    – Xbel
    Dec 12, 2019 at 13:26

1 Answer 1

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This should be in StackOverflow (probably), but here's a quick workaround:

lm = LinearRegression().fit(X, y)

np.linalg.norm(y - lm.predict(X)) ** 2  #RSS, which is what lm.residues_ returns
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