Recent works in Explainable AI mostly address the transparency issue of black-box models or create explanations for any kind (i.e., they are model-agnostic), while leaving interpretable largely underexplored. In this paper, we fill gap by focusing on a specific model, namely pattern-based logistic regression (PLR) binary text classification. We do so because, albeit interpretable, PLR is challe...