Bayesian classification and regression trees for predicting incidence of cryptosporidiosis: quantiles of log residual sums of squares (RSS), deviance and log posterior for training and validation datasets over all accepted trees, for Bayesian regression trees

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 log residual sums of squares (RSS), deviance and log
posterior for training and validation datasets over all accepted trees,
for Bayesian regression trees of the study.