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Table 2 Summary of the average contributions of the significant predictor variables using a Boosted Regression Trees (BRT) model

From: Mapping intra-urban malaria risk using high resolution satellite imagery: a case study of Dar es Salaam

Variable Average relative contribution (%)
Percentage dense/riverine vegetation 29.94
Percentage built-up 26.85
Distance to inland water (m) 8.98
Altitude 8.34
Wetness Index (CTI) 6.61
NDVI 5.44
  1. BRT model developed with cross-validation over 25 bootstraps. Average relative contribution refers to the influence of each variable to the BRT model calculated as the proportion of times that a variable was selected for splitting, weighted by the squared improvement to the model as a result of each split [73]. This was then averaged over the 25 iterations of the BRT model run. This has added to the footnote of Table 2. Variables with zero influence or relative contribution <1 % were dropped from the analysis. Effect of other land cover classes was controlled for