Contextual boosting to explainable SVM classification Universiteit Gent
Finding suitable mechanisms whereby rationale behind support vector machine (SVM) predictions can be known and understood without substantial difficulties is an ongoing challenge. Aiming to find such a mechanism, we look into the contextualization of SVM models. Hence, we propose a novel explainable SVM classifier that makes use of a parallel arrangement of contextualized SVM models for offering predictions that depend on a particular event, ...