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Project overview

Project Overview

The COMBAT (Comprehensive Model Building and Aggregation Toolkit) package is a comprehensive suite of tools designed to address various challenges in predictive modeling, model aggregation, and ensemble learning. It integrates sophisticated algorithms with user-friendly interfaces to empower users in enhancing predictive accuracy, reliability, and interpretability across diverse applications and domains.

Modules of COMBAT:

  1. calibration - a module provides functionality to calibrate the models obtained from the COMBAT package. Calibration is an essential step in ensuring that model predictions are well-calibrated and can be interpreted accurately.

  2. combat - a module facilitates the user to build model ensembles, a powerful technique for improving predictive performance and model robustness.

  3. models - a module provides the LogitModel class, which serves as a core feature in the COMBAT package for logistic regression modeling.

  4. scorecard - a module provides functionality to convert Probability of Default (PD) obtained from models into scores, facilitating risk assessment and decision-making processes.

  5. short_list - a module provides functionality to explore the explanatory power of variables and identify the most influential features for predictive modeling.

  6. transform - a module provides functions for performing Weight of Evidence (WoE) transformation, a common technique in predictive modeling for handling categorical variables.

  7. utilities - a module contains auxiliary functions that support various tasks within the COMBAT package.