diff --git a/doc/src/week48/week48.do.txt b/doc/src/week48/week48.do.txt
index dc17c1c00..7685e7579 100644
--- a/doc/src/week48/week48.do.txt
+++ b/doc/src/week48/week48.do.txt
@@ -58,8 +58,9 @@ wavelets, splines etc.
 
 If our feature space is not easy to separate, as shown in the figure
 here, we can achieve a better separation by introducing more complex
-basis functions. The ideal would be, as shown in the next figure, to, via a specific transformation to 
-obtain a separation between the classes which is almost linear. 
+basis functions. The ideal would be, as shown in the next figure, to,
+via a specific transformation to obtain a separation between the
+classes which is almost linear.
 
 The change of basis, from $x\rightarrow z=\phi(x)$ leads to the same type of equations to be solved, except that
 we need to introduce for example a polynomial transformation to a two-dimensional training set.