Data

Bayesian classification and regression trees for predicting incidence of cryptosporidiosis: quantiles of sensitivity, specificity and log posterior for training and validation datasets over all accepted trees, for Bayesian classification trees

Queensland University of Technology
Adjunct Associate Professor Sama Low Choy (Aggregated by) Professor Wenbiao Hu (Aggregated by) Distinguished Professor Kerrie Mengersen (Aggregated by)
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Licence & Rights:

Open Licence view details
CC-BY

Creative Commons Attribution 3.0
http://creativecommons.org/licenses/by/3.0/au/

© 2011 Hu et al.

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Contact Information

Postal Address:
Dr Wenbiao Hu

w2.hu@qut.edu.au

Full description

This dataset was gathered to predict the spatial distribution of the cryptosporidiosis infection using selected social-ecological factors and climate variables. Predictions were completed using a Bayesian CART (Classification and Regression Trees) model.

The dataset presents the quantiles of sensitivity, specificity and log posterior for training and validation datasets over all accepted trees, for Bayesian classification trees in the study.

Data time period: 2001 to 2011

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153.552920,-9.929730 137.994575,-9.929730 137.994575,-29.178588 153.552920,-29.178588 153.552920,-9.929730

145.7737475,-19.554159

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Identifiers
  • Local : 10378.3/8085/1018.15731