Data Engineering and BI courses are free this week!
This function takes a model object and returns the observed and (optionally) the fitted values in that model.
mod2obspred(model, obs.only = FALSE)A data frame with one column containing the observed and (if obs.only=FALSE, the default) another column containing the predicted values from 'model'.
a model object of class "glm", "gam", "gbm", "GBMFit", "randomForest" or "bart" from which the response variable and fitted (predicted) values can be extracted. Note that, for "randomForest" models, only the out-of-bag prediction is available from the model object (see ?predict.randomForest if you have that package installed), so here you'll get different results if you provide 'model' or the modelled 'obs' (and corresponding 'pred') values.
logical value indicating whether only 'obs' should be obtained (saves computing time when 'pred' not needed -- used e.g. by prevalence). Defaults to FALSE.
A. Marcia Barbosa
prevalence
data(rotif.mods)
mod <- rotif.mods$models[[1]]
obspred <- mod2obspred(mod)
head(obspred)
Run the code above in your browser using DataLab