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-rw-r--r--examples/domain-adaptation/plot_otda_semi_supervised.py4
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()