Explaining models built in H2O

Evaluating single models based on global and local explanations

Photo by Armand Khoury on Unsplash

Machine Learning explainability refers to the ability to understand and interpret the decisions and predictions made by a machine learning model. Explainability is crucial for ensuring the trustworthiness and transparency of machine learning models, particularly in high-stakes situations where the…