Fix typo in JOSS paper
@@ -33,7 +33,7 @@ Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction te
that can be used for visualisation similarly to t-SNE, but also for general non-linear
dimension reduction. UMAP has a rigorous mathematical foundation, but is simple to use,
with a scikit-learn compatible API. UMAP is among the fastest manifold learning
-implementations available -- signifcantly faster than most t-SNE implementations.
+implementations available -- significantly faster than most t-SNE implementations.
UMAP supports a number of useful features, including the ability to use labels
(or partial labels) for supervised (or semi-supervised) dimension reduction,
