| Outcome | R Documentation | 
The outcome class is wrapper around a vector of (mutable) outcomes for ML tasks (supervised learning, causal inference). When an additive tree ensemble is sampled, the outcome used to sample a specific model term is the "partial residual" consisting of the outcome minus the predictions of every other model term (trees, group random effects, etc...).
data_ptrExternal pointer to a C++ Outcome class
new()Create a new Outcome object.
Outcome$new(outcome)
outcomeVector of outcome values
A new Outcome object.
get_data()Extract raw data in R from the underlying C++ object
Outcome$get_data()
R vector containing (copy of) the values in Outcome object
add_vector()Update the current state of the outcome (i.e. partial residual) data by adding the values of update_vector
Outcome$add_vector(update_vector)
update_vectorVector to be added to outcome
None
subtract_vector()Update the current state of the outcome (i.e. partial residual) data by subtracting the values of update_vector
Outcome$subtract_vector(update_vector)
update_vectorVector to be subtracted from outcome
None
update_data()Update the current state of the outcome (i.e. partial residual) data by replacing each element with the elements of new_vector
Outcome$update_data(new_vector)
new_vectorVector from which to overwrite the current data
None
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