“With TreeExplainer, we aim to break out of the so-called black box and understand how #MachineLearning models arrive at their predictions," says @uwcse prof @suinleelab about her lab's recent @NatMachIntell paper.
Details: https://news.cs.washington.edu/2020/01/17/seeing-the-forest-for-the-trees-uw-team-advances-explainable-ai-for-popular-machine-learning-models-used-to-predict-human-disease-and-mortality-risks/ …pic.twitter.com/IkXdZ4kJP5
