diff --git a/server/training.js b/server/training.js
index ea945757..1014c518 100644
--- a/server/training.js
+++ b/server/training.js
@@ -10,7 +10,7 @@ function evaluate(glyphs, classifier) {
 
 Meteor.startup(function() {
   var glyphs = Glyphs.find({'manual.verified': true}).fetch();
-  var sample = _.sample(glyphs, 100);
+  var sample = _.sample(glyphs, 400);
   console.log('Hand-tuned accuracy:', evaluate(sample, hand_tuned_classifier));
 
   var training_data = [];
@@ -42,7 +42,7 @@ Meteor.startup(function() {
   var input = new convnetjs.Vol(1, 1, 8);
   for (var iteration = 0; iteration < 10; iteration++) {
     var loss = 0;
-    var round_data = _.sample(training_data, 1000);
+    var round_data = _.sample(training_data, 4000);
     for (var i = 0; i < round_data.length; i++) {
       assert(input.w.length === round_data[i][0].length);
       input.w = round_data[i][0];
@@ -62,4 +62,15 @@ Meteor.startup(function() {
     return softmax[1] - softmax[0];
   }
   console.log('Neural-net accuracy:', evaluate(sample, net_classifier));
+
+  function combined_classifier(weight) {
+    return function(features) {
+      return hand_tuned_classifier(features) + weight*net_classifier(features);
+    }
+  }
+  var weights = [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1];
+  for (var i = 0; i < weights.length; i++) {
+    console.log('Weight',  weights[i], 'combined accuracy:',
+                evaluate(sample, combined_classifier(weights[i])));
+  }
 });