DOC: replace n by d/2 in LDA equation
@@ -73,7 +73,9 @@ More specifically, for linear and quadratic discriminant analysis,
:math:`P(X|y)` is modelled as a multivariate Gaussian distribution with
density:
-.. math:: p(X | y=k) = \frac{1}{(2\pi)^n |\Sigma_k|^{1/2}}\exp\left(-\frac{1}{2} (X-\mu_k)^t \Sigma_k^{-1} (X-\mu_k)\right)
+.. math:: P(X | y=k) = \frac{1}{(2\pi)^{d/2} |\Sigma_k|^{1/2}}\exp\left(-\frac{1}{2} (X-\mu_k)^t \Sigma_k^{-1} (X-\mu_k)\right)
+
+where :math:`d` is the number of features.
To use this model as a classifier, we just need to estimate from the training
data the class priors :math:`P(y=k)` (by the proportion of instances of class
