Tue 27 Aug 00:14:56 CEST 2024

test/test-cnn.js

@@ -0,0 +1,34 @@
+var data = csv.read('test-cnn-DT.csv'),
+    x,
+    y;
+
+data.shift();
+x=select(data,0,data[0].length-2);
+y=select(data,data[0].length-1);
+
+
+var model = ml.learn({
+  algorithm:ml.ML.CNN,
+  x:x,  // [row1=[col1=[z1,z2,..],col2,..],row2,..]
+  y:y,
+  width:28,
+  height:28,
+  depth:1,
+  normalize:[-.5,.5],
+  iterations:100,
+  layers:[
+    // output Vol is of size 3x4x2 here
+    {type:'input', out_sx:28, out_sy:28, out_depth:1},
+    {type:'conv', sx:5, filters:8, stride:1, pad:2, activation:'relu'},
+    {type:'pool', sx:2, stride:2},
+    {type:'conv', sx:5, filters:16, stride:1, pad:2, activation:'relu'},
+    {type:'pool', sx:3, stride:3},
+    {type:'softmax', num_classes:10}
+  ],
+  trainer : {method: 'adadelta', 
+            l2_decay: 0.001, 
+            batch_size: 10}
+});
+// print(model)
+for(var i=0;i<100;i++)
+  print(y[i],ml.stats.utils.best(ml.classify(model,x[i]).w))