IFT6266 Week 7

With a 50% probability of introducing a horizontal flip, the network gets very close to passing the 80% threshold with early stopping.

Epoch 93
Train Accuracy  0.951350
Valid Accuracy  0.794200

With the addition of per pixel mean and standard deviation normalization the network successfully gets over 80% validation accuracy (barely)!

Epoch 74
Train Accuracy  0.878000
Valid Accuracy  0.803800

The working version of the network can be seen here:
https://github.com/kastnerkyle/ift6266h15/blob/master/convnet.py

Note that addition of ZCA did not seem to help in this case!

With these changes, I will move on to implementing other models/ideas. First up, batch normalization, then spatially sparse convolution and possibly fractional maxpooling.