Imputes p-values from the Z-scores of `ScaledFScore` scores.  Assuming incorrectly
		that the scaled f-scores are normally distributed.

		Parameters
		----------
		X : np.array
			Array of word counts, shape (N, 2) where N is the vocab size.  X[:,0] is the
			positive class, while X[:,1] is the negative class.

		Returns
		-------
		np.array of p-values

def get_p_vals(self, X):
		'''
		Imputes p-values from the Z-scores of `ScaledFScore` scores.  Assuming incorrectly
		that the scaled f-scores are normally distributed.

		Parameters
		----------
		X : np.array
			Array of word counts, shape (N, 2) where N is the vocab size.  X[:,0] is the
			positive class, while X[:,1] is the negative class.

		Returns
		-------
		np.array of p-values

		'''
		z_scores = ScaledFZScore(self.scaler_algo, self.beta).get_scores(X[:,0], X[:,1])
		return norm.cdf(z_scores)