About this document
Evaluating Machine Learning Prediction Reliability by Fauzan is a document available to read on EtoBox.
The article discusses the increasing interest in machine learning (ML) applications in clinical and biological fields, emphasizing the need for reliable predictions to enhance user trust, particularly in healthcare. It reviews existing approaches for assessing the reliability of ML predictions and proposes an integrative framework based on the density and local fit principles to identify reliable and unreliable predictions. The authors aim to consolidate concepts related to ML reliability and provide method
- Author
- Fauzan
- Language
- EN