I have made a binary-classifier using lgbm.The classifier is made on unbalanced dataset. I wanted to see the importance features of the model. There are two types of selecting importance_type -
importance_type (string, optional (default="split")) – How the importance is calculated. If “split”, result contains numbers of times the feature is used in a model. If “gain”, result contains total gains of splits which use the feature.
both split and gain are giving me different feature sets. My question is how to decide which is the better option between split and gain. useful link - lightgbm.plot_importance