Added a modelling algorithm and analysis notebooks #114
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SF_Forest_Forecast uses a Random Forest Regressor to model nonlinearities between variables and predict the amount of GHGs. It also predicts the amount of GHGs emitted in 2017 from 2016 data. Analysis looked at general trends in the amount of GHGs emitted over 2011-2016.
The naive (average value) is only slightly worse than the RF model
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SF_Forest_Forecast uses a Random Forest Regressor to model nonlinearities between variables and predict the amount of GHGs.
It also predicts the amount of GHGs emitted in 2017 from 2016 data.
Analysis looked at general trends in the amount of GHGs emitted over 2011-2016.