gpb.load: Load GPBoost model

In gpboost: Combining Tree-Boosting with Gaussian Process and Mixed Effects Models

Load GPBoost model

Description

Load GPBoost takes in either a file path or model string. If both are provided, Load will default to loading from file Boosters with gp_models can only be loaded from file.

Usage

gpb.load(filename = NULL, model_str = NULL)

Arguments

filename	path of model file
model_str	a str containing the model

Value

gpb.Booster

Author(s)

Fabio Sigrist, authors of the LightGBM R package

Examples

library(gpboost)
data(GPBoost_data, package = "gpboost")

# Train model and make prediction
gp_model <- GPModel(group_data = group_data[,1], likelihood = "gaussian")
bst <- gpboost(data = X, label = y, gp_model = gp_model, nrounds = 16,
               learning_rate = 0.05, max_depth = 6, min_data_in_leaf = 5,
               verbose = 0)
pred <- predict(bst, data = X_test, group_data_pred = group_data_test[,1],
                predict_var= TRUE, pred_latent = TRUE)
# Save model to file
filename <- tempfile(fileext = ".json")
gpb.save(bst,filename = filename)
# Load from file and make predictions again
bst_loaded <- gpb.load(filename = filename)
pred_loaded <- predict(bst_loaded, data = X_test, group_data_pred = group_data_test[,1],
                       predict_var= TRUE, pred_latent = TRUE)
# Check equality
pred$fixed_effect - pred_loaded$fixed_effect
pred$random_effect_mean - pred_loaded$random_effect_mean
pred$random_effect_cov - pred_loaded$random_effect_cov

gpboost documentation built on Oct. 24, 2023, 9:09 a.m.