35 lines
879 B
JavaScript
35 lines
879 B
JavaScript
var data = csv.read('test-cnn-DT.csv'),
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x,
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y;
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data.shift();
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x=select(data,0,data[0].length-2);
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y=select(data,data[0].length-1);
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var model = ml.learn({
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algorithm:ml.ML.CNN,
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x:x, // [row1=[col1=[z1,z2,..],col2,..],row2,..]
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y:y,
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width:28,
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height:28,
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depth:1,
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normalize:[-.5,.5],
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iterations:100,
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layers:[
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// output Vol is of size 3x4x2 here
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{type:'input', out_sx:28, out_sy:28, out_depth:1},
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{type:'conv', sx:5, filters:8, stride:1, pad:2, activation:'relu'},
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{type:'pool', sx:2, stride:2},
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{type:'conv', sx:5, filters:16, stride:1, pad:2, activation:'relu'},
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{type:'pool', sx:3, stride:3},
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{type:'softmax', num_classes:10}
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],
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trainer : {method: 'adadelta',
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l2_decay: 0.001,
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batch_size: 10}
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});
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// print(model)
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for(var i=0;i<100;i++)
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print(y[i],ml.stats.utils.best(ml.classify(model,x[i]).w))
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