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alexander-moore / DS502_Final

DS502 Final Project
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Project Proposal posted #2

Open alexander-moore opened 4 years ago

alexander-moore commented 4 years ago

Please read: https://www.kaggle.com/c/nfl-big-data-bowl-2020/discussion/111918#latest-652437

https://www.kaggle.com/c/nfl-big-data-bowl-2020/data

https://www.kaggle.com/statsbymichaellopez/nfl-tracking-wrangling-voronoi-and-sonars

https://www.kaggle.com/c/nfl-big-data-bowl-2020/discussion/112303#latest-655229

you may need a kaggle acct to see the links above

Hey all Let's discuss here the 502 Final Project Proposal If we've all agreed on the NFL data, let's move forward and talk about what methods we will use. Feel free to edit the document proposal I pushed. one concern I have with the NFL data is how noisy it will be: im worried we will have trouble making any meaningful models since the yardage might be barely-correlated to the data predictors. We can talk about it. idk haha.

ethanprihar commented 4 years ago

i added stuff about the model's we can try, theres a great paper I read once that gave an overview of every deep learning for time series analysis method and like compared the results, but i can't find it. I'll keep looking tho

Edit: found it: https://link.springer.com/article/10.1007/s10618-019-00619-1

mbarger1 commented 4 years ago

I'd recommend we do some sort of regression. I poked around the discussion on the website and it looks like people have been having issues using classification because there are too many classes. I loved the Voronoi diagram link--it's definitely worth exploring some analysis with them, even if it ends up just being exploratory.

I put the description of the error metric into the proposal, but forgot that Latex/MathJax isn't universal to HTML. Anyone know if there's a simple way to get an HTML file to read it, or should I just throw in an image of the formula and call it a day?