no code implementations • 4 May 2023 • Fabian Obster, Christian Heumann, Heidi Bohle, Paul Pechan
We describe how interpretable boosting algorithms based on ridge-regularized generalized linear models can be used to analyze high-dimensional environmental data.
no code implementations • 11 Jan 2023 • Fabian Obster, Heidi Bohle, Paul M. Pechan
Machine learning and statistical modeling methods were used to analyze the impact of climate change on financial wellbeing of fruit farmers in Tunisia and Chile.
1 code implementation • 13 Jun 2022 • Fabian Obster, Christian Heumann
By using component-wise and group-wise gradient boosting at the same time with adjusted degrees of freedom, a model with similar properties as the sparse group lasso can be fitted through boosting.