A new approach to construct basic probability assignment and its applications in data classification
Maninder Kaur, Amit Srivastava · Bulletin of the "Transilvania" University of Braşov. Series III, Mathematics and Computer Science · 2025
In the present work, we have proposed a classification algorithm that uses Dempster Shafer (D-S) evidence theory since it has emerged as an effective tool in handling data classification problems. As basic probability assignment (BPA) is a pre-requisite for applying D-S theory, how to generate it is a hot issue. This paper proposes a novel method for generating basic probability assignments (BPAs) from training data. Dempster Shafer’s (D-S) rule of Combination is utilized for the unification of these BPAs and finally, classify each data item using these unified BPAs. Testing is carried out using some popular benchmark data sets consisting of three classes. Evaluated results show that the classification accuracy is comparatively high.