a Markov Random Field model related to a climate project
This is a Python implementation of the algorithm described in the KDD2019 paper ''Nonparametric Mixture of Sparse Regressions on Spatio-Temporal Data -- An Application to Climate Prediction'', which can be download from here.
Python version: 3.5+
usage:
- download all 3 folders and files (src, data and results) into a folder.
- extract toy data from ''6models_wholeUSA_synthetic3_21random11_36months6to1p_0.01_0.01_8.0_random.rar'' in the data/synthetic/ folder
- run mainsns.py in the src folder.
- the results will be in the results folder.