Tutorial: Implementing TSMA for Unbalanced Data in R

This tutorial provides step-by-step instructions for implementing the Two-stage Sampling Aggregation (TSMA) approach, designed to enhance the performance of predictive models on unbalanced datasets. The TSMA framework integrates bagging concepts, resampling techniques, and advanced machine-learning strategies to improve model accuracy significantly.

R Code

The R code used in this tutorial can be found in the R Code folder.

Example Data

The example data utilized for the tutorial is located in the Data folder.

Demonstration of Our Novel TSMA Model

For a practical demonstration, check out our novel TSMA model applied to the CAMRSA dataset: TSMA Tutorial