Evaluation Methodology for Interpretation Methods of Predictive Quality Models

Quality predictions have great potential in production. However, establishing predictive quality models requires to understand and therefore explain the predictions generated by these models based on production data. Model-independent interpretation methods claim to deliver such insights. As to date there is no approach for assessing the suitability of these methods in production context, we provide a methodology to evaluate them against general requirements as well as requirements specific for the context of process- and product-centered quality prediction. The results show that the proposed methodology is capable to effectively evaluate the interpretation methods based on selected criteria.