Simplified Keras implementation of one class neural network for nonlinear anomaly detection.

The implementation is based on the approach described here: https://arxiv.org/pdf/1802.06360.pdf. I've included several datasets from ODDS (http://odds.cs.stonybrook.edu/) to play with.

pipenv install . should configure a python environment and install all necessary dependencies in the environment.

Running python driver.py within your new python environment (either through CLI or IDE) should kick off training for 50 epochs and generate some output plots.

Two unit tests are defined in test/test_basic.py: building the model, and the quantile loss test based on example in the paper:

Execute pytest test to run.

• Make demo script more flexible
• Add more unit tests