Package index • IBLM

Train

Train iblm

train_iblm_xgb(): Train IBLM Model on XGBoost

Train xgboost

train_xgb_as_per_iblm(): Train XGBoost Model Using the IBLM Model Parameters

Explain

Main Explanation

explain_iblm(): Explain GLM Model Predictions Using SHAP Values

Plotting Functions

beta_corrected_density(): Density Plot of Beta Corrections for a Variable
beta_corrected_scatter(): Scatter Plot of Beta Corrections for a Variable
bias_density(): Density Plot of Bias Corrections from SHAP values
overall_correction(): Plot Overall Corrections from Booster Component
correction_corridor(): Plot GLM vs IBLM Predictions with Different Corridors

Create Plotting Functions

create_beta_corrected_density(): Create Pre-Configured Beta Corrected Density Plot Function
create_beta_corrected_scatter(): Create Pre-Configured Beta Corrected Scatter Plot Function
create_bias_density(): Create Pre-Configured Bias Density Plot Function
create_overall_correction(): Create Pre-Configured Overall Correction Plot Function

Data Transformation

extract_booster_shap(): Extract SHAP values from an xgboost Booster model
data_to_onehot(): Convert Data Frame to Wide One-Hot Encoded Format
shap_to_onehot(): Convert Shap values to Wide One-Hot Encoded Format
beta_corrections_derive(): Compute Beta Corrections based on SHAP values
data_beta_coeff_booster(): Obtain Booster Model Beta Corrections for tabular data
data_beta_coeff_glm(): Obtain GLM Beta Coefficients for tabular data

Predict

predict(<iblm>): Predict Method for IBLM
get_pinball_scores(): Calculate Pinball Scores for IBLM and Additional Models

Data

freMTPLmini: French Motor Insurance Claims Dataset
load_freMTPL2freq(): Load French Motor Third-Party Liability Frequency Dataset

Other

Prepare

split_into_train_validate_test(): Split Dataframe into: 'train', 'validate', 'test'

Theme

theme_iblm(): Custom ggplot2 Theme for IBLM

Check

check_iblm_model(): Check Object of Class `iblm`