diff --git a/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantNearestNeighborsModel.java b/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantNearestNeighborsModel.java
index 45214b47e..39998c05a 100755
--- a/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantNearestNeighborsModel.java
+++ b/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantNearestNeighborsModel.java
@@ -35,8 +35,11 @@ import java.io.PrintStream;
 
 public final class VariantNearestNeighborsModel extends VariantOptimizationModel {
 
-    public VariantNearestNeighborsModel( VariantDataManager _dataManager, final double _targetTITV ) {
-       super( _dataManager, _targetTITV );
+    private final int numKNN;
+
+    public VariantNearestNeighborsModel( VariantDataManager _dataManager, final double _targetTITV, final int _numKNN ) {
+        super( _dataManager, _targetTITV );
+        numKNN = _numKNN;
     }
     
     public void run( final String outputPrefix ) {
@@ -45,7 +48,7 @@ public final class VariantNearestNeighborsModel extends VariantOptimizationModel
 
         final double[] pTrueVariant = new double[numVariants];
 
-        final VariantTree vTree = new VariantTree( 2000 );
+        final VariantTree vTree = new VariantTree( numKNN );
         vTree.createTreeFromData( dataManager.data );
 
         System.out.println("Finished creating the kd-tree.");
@@ -54,7 +57,18 @@ public final class VariantNearestNeighborsModel extends VariantOptimizationModel
             pTrueVariant[iii] = calcTruePositiveRateFromTITV( vTree.calcNeighborhoodTITV( dataManager.data[iii] ) );
         }
 
-        //BUGBUG: need to output pTrueVariant and other metrics in this method
-        //return pTrueVariant;
+        PrintStream outputFile = null;
+        try {
+            outputFile = new PrintStream( outputPrefix + ".knn.optimize" );
+        } catch (Exception e) {
+            e.printStackTrace();
+            System.exit(-1);
+        }
+        for(int iii = 0; iii < numVariants; iii++) {
+            outputFile.print(String.format("%.4f",pTrueVariant[iii]) + ",");
+            outputFile.println( (dataManager.data[iii].isTransition ? 1 : 0)
+                    + "," + (dataManager.data[iii].isKnown? 1 : 0)
+                    + "," + (dataManager.data[iii].isFiltered ? 1 : 0) );
+        }
     }
 }
diff --git a/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantOptimizationModel.java b/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantOptimizationModel.java
index aee28491e..6d85c2f52 100755
--- a/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantOptimizationModel.java
+++ b/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantOptimizationModel.java
@@ -32,6 +32,12 @@ package org.broadinstitute.sting.playground.gatk.walkers.variantoptimizer;
  */
 
 public abstract class VariantOptimizationModel implements VariantOptimizationInterface {
+
+    public enum Model {
+        GAUSSIAN_MIXTURE_MODEL,
+        K_NEAREST_NEIGHBORS
+    }
+
     protected final VariantDataManager dataManager;
     protected final double targetTITV;
 
diff --git a/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantOptimizer.java b/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantOptimizer.java
index c4ce9adf2..5b578325c 100755
--- a/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantOptimizer.java
+++ b/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantOptimizer.java
@@ -7,6 +7,7 @@ import org.broadinstitute.sting.gatk.refdata.RefMetaDataTracker;
 import org.broadinstitute.sting.gatk.walkers.RodWalker;
 import org.broadinstitute.sting.utils.BaseUtils;
 import org.broadinstitute.sting.utils.ExpandingArrayList;
+import org.broadinstitute.sting.utils.StingException;
 import org.broadinstitute.sting.utils.cmdLine.Argument;
 
 /*
@@ -61,10 +62,14 @@ public class VariantOptimizer extends RodWalker<ExpandingArrayList<VariantDatum>
     private String[] FORCED_ANNOTATIONS = null;
     @Argument(fullName="output", shortName="output", doc="The output file name", required=false)
     private String OUTPUT_FILE = "optimizer.data";
-    @Argument(fullName="numGaussians", shortName="nG", doc="The number of Gaussians to be used in the Gaussian mixture model", required=false)
+    @Argument(fullName="numGaussians", shortName="nG", doc="The number of Gaussians to be used in the Gaussian Mixture model", required=false)
     private int NUM_GAUSSIANS = 32;
-    @Argument(fullName="numIterations", shortName="nI", doc="The number of iterations to be performed in the Gaussian mixture model", required=false)
-    private int NUM_ITERATIONS = 5; //BUGBUG: should automatically decided when to stop by looking at how entropy changes with each iteration
+    @Argument(fullName="numIterations", shortName="nI", doc="The number of iterations to be performed in the Gaussian Mixture model", required=false)
+    private int NUM_ITERATIONS = 10;
+    @Argument(fullName="knn", shortName="knn", doc="The number of nearest neighbors to be used in the k-Nearest Neighbors model", required=false)
+    private int NUM_KNN = 2000;
+    @Argument(fullName = "optimization_model", shortName = "om", doc = "Optimization calculation model to employ -- GAUSSIAN_MIXTURE_MODEL is currently the default, while K_NEAREST_NEIGHBORS is also available for small callsets.", required = false)
+    private VariantOptimizationModel.Model OPTIMIZATION_MODEL = VariantOptimizationModel.Model.GAUSSIAN_MIXTURE_MODEL;
 
 
     /////////////////////////////
@@ -179,8 +184,19 @@ public class VariantOptimizer extends RodWalker<ExpandingArrayList<VariantDatum>
         dataManager.normalizeData(); // Each data point is now [ (x - mean) / standard deviation ]
         
         // Create either the Gaussian Mixture Model or the Nearest Neighbors model and run it
-        final VariantOptimizationModel gmm = new VariantGaussianMixtureModel( dataManager, TARGET_TITV, NUM_GAUSSIANS, NUM_ITERATIONS  );
-        gmm.run( OUTPUT_FILE );
+        VariantOptimizationModel theModel;
+        switch (OPTIMIZATION_MODEL) {
+            case GAUSSIAN_MIXTURE_MODEL:
+                theModel = new VariantGaussianMixtureModel( dataManager, TARGET_TITV, NUM_GAUSSIANS, NUM_ITERATIONS  );
+                break;
+            case K_NEAREST_NEIGHBORS:
+                theModel = new VariantNearestNeighborsModel( dataManager, TARGET_TITV, NUM_KNN );
+                break;
+            default:
+                throw new StingException("Variant Optimization Model is unrecognized. Implemented options are GAUSSIAN_MIXTURE_MODEL and K_NEAREST_NEIGHBORS");
+        }
+
+        theModel.run( OUTPUT_FILE );
     }
 
 }