tidypredict_combine_trees: Combine per-tree expressions into a model's prediction

In tidypredict: Run Predictions Inside the Database

Combine per-tree expressions into a model's prediction

Description

tidypredict_trees() returns one expression per tree. Turning those back into the model's prediction is not simply summing or averaging them, and the rule differs by backend: mboost::blackboost() needs an offset and a shrinkage factor, CatBoost needs a scale and a bias, aorsf needs a guard that returns NA for an incomplete row, and boosters then apply their objective's inverse link on top.

This generic holds that rule, so a caller that has split the trees apart can put them back together without knowing which backend it is holding.

Usage

tidypredict_combine_trees(x, trees, ...)

Arguments

x	A fitted model object.
trees	A list of expressions, one per tree, in the order tidypredict_trees() returns them. Typically either that return value itself, or symbols naming the columns the individual trees were written to.
...	Additional arguments passed to methods.

Details

The point of separating trees from this function is that a caller can compute each tree into its own column, for a database to evaluate in parallel, and then pass symbols referring to those columns rather than the expressions themselves. The combination is the same either way.

A caller may also pass fewer elements than the model has trees, where each one is a subtotal of several trees added together. This is what a caller does to keep any single generated expression short enough for a database parser. Every method supports it: those that average take the divisor from the model rather than from length(trees), and the rest sum. The one thing a caller must not do is reorder or drop trees, since a method is free to treat position as meaningful.

Every ensemble satisfies tidypredict_combine_trees(x, tidypredict_trees(x)) computing the same values as tidypredict_fit(x), and that identity is what the tests for these methods assert.

Not every ensemble has a method. C50::C5.0() boosting combines its trees by a confidence-weighted vote that yields a class label, so there is no arithmetic to apply to per-tree numbers and no method is provided.

Value

A single language object.

See Also

tidypredict_extractors for the generics that produce trees, including a table of which model classes implement them, and tidypredict_metadata for what the combined value means.

Examples

model <- randomForest::randomForest(mpg ~ ., data = mtcars, ntree = 3)

trees <- tidypredict_trees(model)
tidypredict_combine_trees(model, trees)

# Or referring to columns the trees were written to first.
tidypredict_combine_trees(model, rlang::syms(c("t1", "t2", "t3")))

tidypredict documentation built on Oct. 18, 2026, 5:06 p.m.