Interpretation

Machine Learning (ML) models are often complex and difficult to interpret due to their “black-box” characteristics. Interpretability of a ML model is usually defined as the degree to which a human can understand the cause of decisions reached by a ML …

Machine learning based predictive models have been used in different areas of everyday life for decades. However, with the recent availability of big data, new ways emerge on how to interpret the decisions of machine learning models. In addition to …