Visual color matching for GBM

Quick answer：

GBM, or Gradient Boosting Machine, is a machine learning algorithm used for regression and classification tasks. Visual color matching in this context refers to the process of selecting appropriate colors to represent the output of a GBM model, such as for feature importance visualization. This involves understanding the model's output and the psychological and cultural aspects of color perception to create an informative and aesthetically pleasing visualization.