The GBMVis system was created to help experts understand and interpret the complex gradient boosting machine (GBM) model. By visualizing the features and structure of the boosting trees, GBMVis allows for quick analysis of the GBM's prediction process. This system is particularly useful for fields like medical diagnosis and financial analytics, where transparent predictions are crucial. The researchers demonstrated the effectiveness of GBMVis in a real dataset, showing its potential to improve the interpretability of GBM models.