My goal with this project was to see if you could use PNG compression to do decent image classification. I was inspired by a recent paper that used GZip compression and kNN to do sentiment analysis on text. I figured it would be fun to try something like this using Fashion MNIST.
This didn't work very well. On average, there are two categories that half of the labeled sets seem to fall into in terms of compressed length. I didn't do anything with kNN as it would likely not result in much further differentiation given the bimodal homogenous nature of the results. Still, this was a fun experiment.
For fun, I also tried this with MNIST (code not included, but all you need to do is use the MNIST dataset identifier from MLDatasets and use string(k) for the label since there is no classnames method for MNIST data).
