Researcher:  Puseletso Maile, University of the Witwatersrand, Johannesburg
Supervisor:  Prof. Rod Alence, University of the Witwatersrand, Johannesburg

In 2010 leaders from developed nations pledged to contribute a $100 billion year on year towards climate finance for developing countries. The reason for this is because developed countries are the biggest polluters and because developing countries are most vulnerable to climate change and because they do not have the resources to respond to extreme weather conditions.  This study assesses trends in climate finance for developing countries looking at whether: There was a significant increase in climate finance after 2010. Trends in climate finance at regional level and income group level. If climate finance provided for mitigation was higher than for adaptation. And what are determinants for climate finance.

This study applied three machine learning algorithms namely Linear Regression (LR), Random Forest (RF), and Support Vector Machine (SVM) to predict precipitation in KwaZulu Natal Province, South Africa. The result shows that SVM had the best performance followed by RF and finally LR.