pipelearner
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Feature: wrapper functions to "predict" and "score"
In general, a user will want to predict values and score/evaluated their fit after learning all models via learn()
. The exact functions to do this are many. However, pipeable functions could be written that takes the tibble coming from learn()
as well as a function that will take the relevant columns (e.g., test, target, and fit), and output the predicted values. It will then be the responsibility of the user to create a function that accepts these arguments.
e.g.,...
pl %>% learn() %>%
pl_predict("test_hat", FUN = function(test, target, fit) {
# etc... to produce vectors of fitted values
}) %>%
pl_score("test_rsqr", FUN = function(test, target, test_hat) {
# etc...
})