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Create Pre-Configured Beta Corrected Scatter Plot Function

Source: R/create_beta_correction_plot_functions.R
create_beta_corrected_scatter.Rd

Factory function that returns a plotting function with data pre-configured.

Usage

create_beta_corrected_scatter(data_beta_coeff, data, iblm_model)

Arguments

data_beta_coeff

Dataframe. Contains the corrected beta coefficients for each row of the data.

data

Dataframe. The testing data.

iblm_model

Object of class 'iblm'.

Value

Function with signature function(varname, q = 0, color = NULL, marginal = FALSE).

See also

[beta_corrected_scatter()]

Examples

# ------- prepare iblm objects required -------

df_list <- freMTPLmini |> split_into_train_validate_test(seed = 9000)

iblm_model <- train_iblm_xgb(
  df_list,
  response_var = "ClaimRate",
  family = "poisson"
)

test_data <- df_list$test
shap <- extract_booster_shap(iblm_model$booster_model, test_data)
wide_input_frame <- data_to_onehot(test_data, iblm_model)
shap_wide <- shap_to_onehot(shap, wide_input_frame, iblm_model)
beta_corrections <- beta_corrections_derive(shap_wide, wide_input_frame, iblm_model)
data_glm <- data_beta_coeff_glm(test_data, iblm_model)
data_booster <- data_beta_coeff_booster(test_data, beta_corrections, iblm_model)
data_beta_coeff <- data_glm + data_booster

# ------- demonstration of functionality -------

# create_beta_corrected_scatter() can create function of type 'beta_corrected_scatter'
my_beta_corrected_scatter <- create_beta_corrected_scatter(data_beta_coeff, test_data, iblm_model)

# this custom function then acts as per beta_corrected_scatter()
my_beta_corrected_scatter(varname = "VehAge")
#> `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'