Excuse me while I organize all the scripts...
A collection of scripts for investigating decision margins in neural networks.
- input_pipe.py We read in binary data (cat and dog images) using the new Tensorflow Dataset api
- crop.py Helper script to crop images. Going to be included in input_pipe.py eventually
- closest_pair.py A script to find the pair of images with the least euclidean distance seperating them. However, this script is inefficient with large (5k+) datasets, and needs to be rewritten using CUDA
- conv_net.py Simple convolutional network model and training for testing.
- lin_reg.py For testing.
- image_generator.py A script to generate a series of images within an n-sphere around an existing image. We use this in an attempt to artifically modify the decision margin of our network.
When is Nearest Neighbor Meaningful?:https://members.loria.fr/MOBerger/Enseignement/Master2/Exposes/beyer.pdf
"...that under certain reasonable assumptions on the data distribution, the ratio of the distances of the nearest and farthest neighbors to a given target in high dimensional space is almost 1 for a wide variety of data distributions and distance functions."