8000 [MRG+1] FIX Use slinear interpolation for isotonic regression by raghavrv · Pull Request #4111 · scikit-learn/scikit-learn · GitHub
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[MRG+1] FIX Use slinear interpolation for isotonic regression #4111

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Merged
merged 1 commit into from
Jan 17, 2015

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raghavrv
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Fixes #4101

@agramfort
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+1 for merge

@raghavrv raghavrv changed the title FIX Use slinear interpolation for isotonic regression [MRG+1] FIX Use slinear interpolation for isotonic regression Jan 17, 2015
@GaelVaroquaux
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LGTML. Merging.

GaelVaroquaux added a commit that referenced this pull request Jan 17, 2015
[MRG+1] FIX Use slinear interpolation for isotonic regression
@GaelVaroquaux GaelVaroquaux merged commit 7962412 into scikit-learn:master Jan 17, 2015
@raghavrv raghavrv deleted the slinear_isotonic branch January 17, 2015 13:20
@@ -228,7 +228,7 @@ def _build_f(self, X, y):
.format(self.out_of_bounds))

bounds_error = self.out_of_bounds == "raise"
self.f_ = interpolate.interp1d(X, y, kind='linear',
self.f_ = interpolate.interp1d(X, y, kind='slinear',
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you can (and should) now also undo the workaround in line 321, i.e., adding np.finfo(float).resolution to self.X_min_, and remove the comment in 319-320

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Thanks! fixed in #4113...

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Use slinear interpolation in Isotonic
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