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Result of hyperparameter tuning - small changes
Inspiration
everyone on the team has worked in some sort of ai/physics field, and has some experience using ai to further our knowledge about a subject.
What it does
Tried different methods - hyperparameter tuning, curve fitting, and trying to understand the underlying physics behind what is going on.
How we built it
python
Challenges we ran into
decision trees were too simple, and did not contribute much to the accuracy, after some slight improvements.
Accomplishments that we're proud of
we learned what the ETAS equation does and what its pitfalls are, along with possible replacements for that model. We implemented a hyperparameter tuning method into the starter code, which increased the accuracy some.
