Merge branch 'master' of https://github.com/mimno/Mallet

Author: mimno

src/cc/mallet/topics/tui/TopicTrainer.java

@@ -147,7 +147,7 @@ public class TopicTrainer {
          "The number of iterations to run before first estimating dirichlet hyperparameters.", null);
 
     static CommandOption.Boolean useSymmetricAlpha = new CommandOption.Boolean(TopicTrainer.class, "use-symmetric-alpha", "true|false", false, false,
-         "Only optimize the concentration parameter of the prior over document-topic distributions. This may reduce the number of very small, poorly estimated topics, but may disperse common words over several topics.", null);
+         "Optimize the concentration parameter (SumAlpha) of the prior over document-topic distributions while keeping it symmetric. This may reduce the number of very small, poorly estimated topics, but may disperse common words over several topics.", null);
 
     static CommandOption.Double alpha = new CommandOption.Double(TopicTrainer.class, "alpha", "DECIMAL", true, 5.0,
          "SumAlpha parameter: sum over topics of smoothing over doc-topic distributions. alpha_k = [this value] / [num topics]",null);

src/cc/mallet/types/Dirichlet.java

@@ -555,6 +555,8 @@ public static void testSymmetricConcentration(int numDimensions, int numObservat
 
 	/** 
 	 * Learn Dirichlet parameters using frequency histograms
+	 * described by Hanna Wallach in "Structured Topic Models for Language" (2008), section 2.4
+	 * Method 1: Using the Digamma Recurrence Relation (pp. 27-28)
 	 * 
 	 * @param parameters A reference to the current values of the parameters, which will be updated in place
 	 * @param observations An array of count histograms. <code>observations[10][3]</code> could be the number of documents that contain exactly 3 tokens of word type 10.
@@ -571,6 +573,8 @@ public static double learnParameters(double[] parameters,
 
 	/** 
 	 * Learn Dirichlet parameters using frequency histograms
+	 * described by Hanna Wallach in "Structured Topic Models for Language", section 2.4
+	 * Method 1: Using the Digamma Recurrence Relation (pp. 27-28) and gamma hyperpriors (section 2.5, pp. 37-39)
 	 * 
 	 * @param parameters A reference to the current values of the parameters, which will be updated in place
 	 * @param observations An array of count histograms. <code>observations[10][3]</code> could be the number of documents that contain exactly 3 tokens of word type 10.