README

Dear Reader and Judge,

This document explains how to run the Protego code and how to access the prototype demo.

What is going on?

The "Protego_backend_alpha.py" script plays a role in the backend of PROTEGOs dashboard for trend analysis and reputation management.

The prototype demo can be seen at: http://www.robots.ox.ac.uk/~favour/protego

Machine Learning Algorithm

Method: GradientBoostingClassifier

Why: It performed the best in our parameter analysis.

Others Tested: AdaBoost, XGBoost

Why Abandoned: The were outperformed by GradientBoostingClassifier on various parameters in our analysis.

Insight: It is easy to get the performance up to 74% and difficult to get the performance alot higher. It is similarly hard to perform at more than 80% on the training set with the methods we attempted.

Our Assumptions: We restricted ourselves to usin the data given. We restricted ourselves to ML approaches that we can train in a short amount of time, e.g. Deep Learning is too GPU-computation heavy.

How to run the code

1. Open a python 3 environment with the following libraries installed: tqdm, sklearn, numpy, scipy, nltk

2. Run the python 3 file "Protego_backend_alpha.py" scans through the training data and evaluates on the test data.

3. This gives a model, which can classify the relationship between the header and the body of texts.