[MRG] Fix quadruplets scoring #220
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metric_learn/base_metric.py
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| @@ -641,4 +641,4 @@ def score(self, quadruplets): | |||
| score : float | |||
| The quadruplets score. | |||
| """ | |||
| return - np.mean(self.predict(quadruplets)) | |||
| return np.mean((self.predict(quadruplets) + 1) / 2) | |||
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This should be equivalent to pred.mean() / 2 + 0.5, which is more efficient to compute.
I'd also add a comment explaining that the prediction is a vector of either -1 or 1 values, and that we're rescaling to [0, 1].
bellet
approved these changes
Jun 14, 2019
|
If everybody agrees, I think we are good to merge |
|
Agreed, merged. |
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There was a problem with scoring in LSML: this PR fixes it (and adds a non-regression test as well as a small test for prediction for pairs learners)