Outlier Detection UI

This is a simple UI for running different outlier detection algorithms on synthesized dataset. The backend of this UI is based on the pyod library and thus this UI can also be viewed as a simple demonstration interface of pyod (although unofficially developed).

Screenshots

Just opened with a splash,

Detection results displayed,

Usage

1. Install dependencies in requirements.txt.
2. run app.py.
3. In the PARAMETERS panel, set the parameters.
4. Press RUN to see the results.

Fixing the Random Seed and switching the models allow you to compare the performances of different models on the same dataset. Changing the seed or the parameters of the dataset (e.g., Ratio of Outliers, Feature Dims) will cause a different dataset to be loaded.

TODO

1. Add the EXPORT button to allow dataset & detection results & model export.
2. ...