# Interpretable Boosted Linear Models

## Documentation for package ‘IBLM’ version 1.0.2

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

beta_corrected_density | Density Plot of Beta Corrections for a Variable
beta_corrected_scatter | Scatter Plot of Beta Corrections for a Variable
beta_corrections_derive | Compute Beta Corrections based on SHAP values
bias_density | Density Plot of Bias Corrections from SHAP values
check_iblm_model | Check Object of Class 'iblm'
correction_corridor | Plot GLM vs IBLM Predictions with Different Corridors
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_beta_coeff_booster | Obtain Booster Model Beta Corrections for tabular data
data_beta_coeff_glm | Obtain GLM Beta Coefficients for tabular data
data_to_onehot | Convert Data Frame to Wide One-Hot Encoded Format
explain_iblm | Explain GLM Model Predictions Using SHAP Values
extract_booster_shap | Extract SHAP values from an xgboost Booster model
extract_booster_shap.xgb.Booster | Extract SHAP values from an xgboost Booster model
freMTPLmini | French Motor Insurance Claims Dataset
get_pinball_scores | Calculate Pinball Scores for IBLM and Additional Models
load_freMTPL2freq | Load French Motor Third-Party Liability Frequency Dataset
overall_correction | Plot Overall Corrections from Booster Component
predict.iblm | Predict Method for IBLM
shap_to_onehot | Convert Shap values to Wide One-Hot Encoded Format
split_into_train_validate_test | Split Dataframe into: 'train', 'validate', 'test'
theme_iblm | Custom ggplot2 Theme for IBLM
train_iblm_xgb | Train IBLM Model on XGBoost
train_xgb_as_per_iblm | Train XGBoost Model Using the IBLM Model Parameters