8000 Nca temp by wdevazelhes · Pull Request #1 · wdevazelhes/scikit-learn · GitHub
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Nca temp #1

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Nca temp #1

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010a211
minor corrections in docstring
Oct 27, 2017
9f1157d
minor corrections in docstring
Oct 27, 2017
22838c5
remove comment
Oct 27, 2017
8a9ff5b
Add verbose during iterations
Oct 30, 2017
76f3544
Update code according to code review:
Oct 31, 2017
0cee29d
Remove _make_masks and use OneHotEncoder instead
Oct 31, 2017
507b763
precise that distances are squared
Oct 31, 2017
f6d0973
simplify tests and remove None parameter in nca
Oct 31, 2017
4c0494d
remove useless None
Oct 31, 2017
fb8cefa
simplify tests
Oct 31, 2017
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William de Vazelhes committed Oct 27, 2017
commit 22838c5ddb27d0283254b465594172bcaaa6c52c
2 changes: 1 addition & 1 deletion sklearn/neighbors/nca.py
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Original file line number Diff line number Diff line change
Expand Up @@ -445,7 +445,7 @@ def _loss_grad_lbfgs(self, transformation, X, y, diffs,
ci = masks[:, y[i]]
p_i_j = soft[ci]
not_ci = np.logical_not(ci)
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can't we just use ~ci and avoid defining this variable?

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Yes you are right, I changed it

diff_ci = diffs[i, ci, :] # n_samples * n_features
diff_ci = diffs[i, ci, :]
diff_not_ci = diffs[i, not_ci, :]
sum_ci = diff_ci.T.dot(
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again, sum_ci and sum_not_ci are distances

(p_i_j[:, np.newaxis] * diff_embedded[ci, :]))
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