2015-06-11T21:30:37 n2552

Bayesian classification and regression trees for predicting incidence of cryptosporidiosis: top 5 of the set of 16 best trees based on sensitivity, specificity, accuracy and deviance

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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 top 5 of the set of 16 trees (based on sensitivity, specificity, accuracy and deviance) for Bayesian classification trees.

Location of data collection

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

Publications

Hu, Wen, O'Leary, Rebecca, Mengersen, Kerrie, & Low-Choy, Sama (2011) Bayesian Classification and regression trees for predicting incidence of cryptosporidiosis. PLoS ONE, 6(8), pp. 1-8. http://eprints.qut.edu.au/52459/

Research areas

Cryptosporidium
Crytposporidiosis
Infectious diseases
Spatial distribution
Bayes theorem
Probability distribution
Decision trees
Bayesian

Cite this collection

Hu, Wenbiao; O'Leary, Rebecca A.; Mengersen, Kerrie; Choy, Samantha Low (2013): Top 5 of the set of 16 best trees (based on sensitivity, specificity, accuracy and deviance) for Bayesian classification trees. Table_2.xls. PLOS ONE. 10.1371/journal.pone.0023903.t002

Related information

Rebecca O'Leary, Research collaborator http://goo.gl/LqhdR6

Access the data

Licence


Creative Commons Attribution 4.0 (CC-BY)
http://creativecommons.org/licenses/by/4.0/

Copyright

© 2011 Hu et al.

Dates of data collection

From 2001 to 2011

Connections

Was collected by
Kerrie Mengersen  (Researcher)
Sama Low Choy  (Researcher)
Wenbiao Hu  (Researcher)

Contacts

Other

Date record created:
2014-07-03T14:01:46
Date record modified:
2015-06-11T21:30:37
Record status:
Published - Open Access