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Update classifier to included trained neural net

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Shaunak Kishore
2015-09-13 00:35:41 -04:00
parent 515014d39a
commit 9f0a69554c
4 changed files with 22 additions and 4 deletions
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17
lib/classifier.js Normal file
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@ -0,0 +1,17 @@
Meteor.startup(function() {
var weight = 0.8;
var dimensions = 8;
var input = new convnetjs.Vol(1, 1, dimensions);
var net = new convnetjs.Net();
net.fromJSON(TRAINED_NEURAL_NET);
function net_classifier(features) {
input.w = features;
var softmax = net.forward(input).w;
return softmax[1] - softmax[0];
}
this.combined_classifier = function(features) {
return hand_tuned_classifier(features) + weight*net_classifier(features);
}
});

1
lib/net.js Normal file
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2
lib/stroke_extractor.js
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@ -503,7 +503,7 @@ this.get_glyph_render_data = function(glyph, manual_bridges, classifier) {
} }
} }
var log = []; var log = [];
var bridges = get_bridges(endpoints, classifier || hand_tuned_classifier); var bridges = get_bridges(endpoints, classifier || combined_classifier);
var strokes = extract_strokes( var strokes = extract_strokes(
paths, endpoints, manual_bridges || bridges, log); paths, endpoints, manual_bridges || bridges, log);
var expected = UNIHAN_STROKE_COUNTS[glyph.name]; var expected = UNIHAN_STROKE_COUNTS[glyph.name];

6
server/training.js
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@ -8,7 +8,7 @@ function evaluate(glyphs, classifier) {
return num_correct/glyphs.length; return num_correct/glyphs.length;
} }
Meteor.startup(function() { function train_neural_net() {
var glyphs = Glyphs.find({'manual.verified': true}).fetch(); var glyphs = Glyphs.find({'manual.verified': true}).fetch();
var sample = _.sample(glyphs, 400); var sample = _.sample(glyphs, 400);
console.log('Hand-tuned accuracy:', evaluate(sample, hand_tuned_classifier)); console.log('Hand-tuned accuracy:', evaluate(sample, hand_tuned_classifier));
@ -52,7 +52,7 @@ Meteor.startup(function() {
} }
console.log('Iteration', iteration, 'mean loss:', loss/round_data.length); console.log('Iteration', iteration, 'mean loss:', loss/round_data.length);
} }
console.log('Trained neural network.'); console.log('Trained neural network:', JSON.stringify(net.toJSON()));
function net_classifier(features) { function net_classifier(features) {
assert(input.w.length === features.length); assert(input.w.length === features.length);
@ -73,4 +73,4 @@ Meteor.startup(function() {
console.log('Weight', weights[i], 'combined accuracy:', console.log('Weight', weights[i], 'combined accuracy:',
evaluate(sample, combined_classifier(weights[i]))); evaluate(sample, combined_classifier(weights[i])));
} }
}); }