tune_ll_regression_forest: Local linear forest tuning

In grf: Generalized Random Forests

Local linear forest tuning

Description

Finds the optimal ridge penalty for local linear prediction.

Usage

tune_ll_regression_forest(
  forest,
  linear.correction.variables = NULL,
  ll.weight.penalty = FALSE,
  num.threads = NULL,
  lambda.path = NULL
)

Arguments

forest	The forest used for prediction.
linear.correction.variables	Variables to use for local linear prediction. If left null, all variables are used. Default is NULL.
ll.weight.penalty	Option to standardize ridge penalty by covariance (TRUE), or penalize all covariates equally (FALSE). Defaults to FALSE.
num.threads	Number of threads used in training. If set to NULL, the software automatically selects an appropriate amount.
lambda.path	Optional list of lambdas to use for cross-validation.

Value

A list of lambdas tried, corresponding errors, and optimal ridge penalty lambda.

grf documentation built on Oct. 1, 2023, 1:07 a.m.