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CEST Proceedings are published under the ISSN 2944-9820.

Meteorological Data Science: exploiting causality discovery in time-series for knowledge discovery and improved forecasting

Gkikas A., (Corresponding) Maragoudakis M.

Topic:

Enviornmental data analysis and modelling

Climate change and its impact on everyday life still remains one of the greatest challenge of our era. The complex nature of climate data addresses the use of data science techniques to provide predictive analytics to the task at hand. While most existing approaches exploit correlation between...Read more

Keywords:

Data Science, Causal Inference, Time-Series Analysis, Graph Analysis, Feature Selection

DOI:

https://doi.org/10.30955/gnc2019.00828

Conference:

CEST2019

Paper ID:

cest2019_00828