Create ForestModel object

Create a forest model object

This function is intended for advanced use cases in which users require detailed control of sampling algorithms and data structures. Minimal input validation and error checks are performed – users are responsible for providing the correct inputs. For tutorials on the "proper" usage of the stochtree's advanced workflow, we provide several vignettes at https://stochtree.ai/

Usage

createForestModel(forest_dataset, forest_model_config, global_model_config)

Arguments

forest_dataset

ForestDataset object, used to initialize forest sampling data structures

forest_model_config

ForestModelConfig object containing forest model parameters and settings

global_model_config

GlobalModelConfig object containing global model parameters and settings

Value

ForestModel object

Examples

num_trees <- 100
n <- 100
p <- 10
alpha <- 0.95
beta <- 2.0
min_samples_leaf <- 2
max_depth <- 10
feature_types <- as.integer(rep(0, p))
X <- matrix(runif(n*p), ncol = p)
forest_dataset <- createForestDataset(X)
forest_model_config <- createForestModelConfig(feature_types=feature_types,
                                               num_trees=num_trees, num_features=p,
                                               num_observations=n, alpha=alpha, beta=beta,
                                               min_samples_leaf=min_samples_leaf,
                                               max_depth=max_depth, leaf_model_type=1)
#> Warning: `variable_weights` not provided, will be assumed to be equal-weighted
global_model_config <- createGlobalModelConfig(global_error_variance=1.0)
forest_model <- createForestModel(forest_dataset, forest_model_config, global_model_config)