Published January 25, 2023
| Version 1
Dataset
Open
Summary ouput data - Wasteaware Cities Benchmark Indicators - WABI 2023 - Global data analytics - Machine learning vs. Non-linear Regression
Authors/Creators
- 1. University of Leeds
- 2. Imperial College London
- 3. 0000-0002-6892-2204
Description
This is the output dataset for the research publication "Socio-economic development drives solid waste management performance in cities: A global analysis using machine learning". It features
- Metadata info used by R codes
- Summary of results for two modelling approaches (machine learning: Conditional random-forest and non-linear regression)
The independent variables dataset analysed here refer to specific indicators of the WABI methodology (https://www.sciencedirect.com/science/article/pii/S0956053X14004905) that generates solid waste management and resource recovery profiles for cities. It was applied here for 40 cities around the world. The data input are available here: 10.5281/zenodo.7570174
Notes
Files
Files
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