DOC fix a typo in plot_varimax_fa.py
typo in an example
@@ -7,7 +7,7 @@ Investigating the Iris dataset, we see that sepal length, petal
length and petal width are highly correlated. Sepal width is
less redundant. Matrix decomposition techniques can uncover
these latent patterns. Applying rotations to the resulting
-components does not inherently improve the predictve value
+components does not inherently improve the predictive value
of the derived latent space, but can help visualise their
structure; here, for example, the varimax rotation, which
is found by maximizing the squared variances of the weights,
