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I'm very surprised that this worked with the small amount of training data he provided! (he "provided the algorithm ten images containing hand written digits...
by zodiac 10y ago
I'm very surprised that this worked with the small amount of training data he provided! (he "provided the algorithm ten images containing hand written digits..." - if we generously estimate that each image has 10 training images, that's only 100 training examples)
- wforfang 10y agoAuthor here: I'm equally surprised it worked so well with such little training data. Each image contained 1 example of each character (18 total characters * 10 images = 180 examples). Having said that, I don't think it would generalize well to other people's handwriting until I provided a (lot) more training data.
- zodiac 10y agoDid you use any regularization? Did you train until the training accuracy converged? I feel like the network has enough capacity to overfit 180 training samples
- wforfang 10y agoI experimented with a few regularization factors and ultimately settled on a lambda of 0.1. Rather than using a stopping criteria, I ran a fixed number of training iterations (~100) and just eyeballed the cost function results. Since my total training time was fairly brief (~2 minutes, tops), I had the luxury of designing the ANN somewhat heuristically.