The Legacy of Spatial Apartheid Machine Learning Challenge Data Version 1
Domaine:
socioeconomicgeospatialType de record:
dataset
Créateur:
SefGebMooKle
Éditeur:
ICP
Hôte:
The dataset was created from data classifying neighbourhoods in South Africa According to 4 neighbourhood types: Wealthy (a combination of the classes Suburb, Smallholdings, Farm), Non-wealthy (combination of Township, Informal area, Collective living Quarters, Village), Non-Residential (combination of Industrial area, Commercial land, Parks and Recreational Areas, Vacant) and Background.
These data are to be used for a machine learning challenge put on by Zindi.
The specific application the authors created the larger dataset for is to enable researchers and policymakers to quantify the effects of spatial apartheid over time, for the specific purpose of helping to uncover and working to reverse its effects. Those data will be available at a later date. Datasets: DS1: The Legacy of Spatial Apartheid Machine Learning Challenge Data There are no data files to be downloaded. The only way to access these data is through applying.Inquiries about the larger dataset should be submitted to icpsr-help@umich.edu referencing RCMD and the DAIR data.
These data are to be used for a machine learning challenge put on by Zindi.
The specific application the authors created the larger dataset for is to enable researchers and policymakers to quantify the effects of spatial apartheid over time, for the specific purpose of helping to uncover and working to reverse its effects. Those data will be available at a later date. Datasets: DS1: The Legacy of Spatial Apartheid Machine Learning Challenge Data There are no data files to be downloaded. The only way to access these data is through applying.Inquiries about the larger dataset should be submitted to icpsr-help@umich.edu referencing RCMD and the DAIR data.