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| author | Oleksii Kachaiev <kachayev@gmail.com> | 2023-05-03 10:36:09 +0200 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2023-05-03 10:36:09 +0200 |
| commit | 2aeb591be6b19a93f187516495ed15f1a47be925 (patch) | |
| tree | 9a6f759856a3f6b2d7c6db3514927ba3e5af10b5 /examples/domain-adaptation/plot_otda_semi_supervised.py | |
| parent | 8a7035bdaa5bb164d1c16febbd83650d1fb6d393 (diff) | |
[DOC] Corrected spelling errors (#467)
* Fix typos in docstrings and examples
* A few more fixes
* Fix ref for `center_ot_dual` function
* Another typo
* Fix titles formatting
* Explicit empty line after math blocks
* Typo: asymmetric
* Fix code cell formatting for 1D barycenters
* Empirical
* Fix indentation for references
* Fixed all WARNINGs about title formatting
* Fix empty lines after math blocks
* Fix whitespace line
* Update changelog
* Consistent Gromov-Wasserstein
* More Gromov-Wasserstein consistency
---------
Co-authored-by: Rémi Flamary <remi.flamary@gmail.com>
Diffstat (limited to 'examples/domain-adaptation/plot_otda_semi_supervised.py')
| -rw-r--r-- | examples/domain-adaptation/plot_otda_semi_supervised.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/examples/domain-adaptation/plot_otda_semi_supervised.py b/examples/domain-adaptation/plot_otda_semi_supervised.py index 478c3b8..278c8dd 100644 --- a/examples/domain-adaptation/plot_otda_semi_supervised.py +++ b/examples/domain-adaptation/plot_otda_semi_supervised.py @@ -50,7 +50,7 @@ ot_sinkhorn_semi = ot.da.SinkhornTransport(reg_e=1e-1) ot_sinkhorn_semi.fit(Xs=Xs, Xt=Xt, ys=ys, yt=yt) transp_Xs_sinkhorn_semi = ot_sinkhorn_semi.transform(Xs=Xs) -# semi supervised DA uses available labaled target samples to modify the cost +# semi supervised DA uses available labeled target samples to modify the cost # matrix involved in the OT problem. The cost of transporting a source sample # of class A onto a target sample of class B != A is set to infinite, or a # very large value @@ -92,7 +92,7 @@ pl.subplot(2, 2, 4) pl.imshow(ot_sinkhorn_semi.cost_, interpolation='nearest') pl.xticks([]) pl.yticks([]) -pl.title('Cost matrix - semisupervised DA') +pl.title('Cost matrix - semi-supervised DA') pl.tight_layout() |