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These belief function methods which can be applied within the machine learning domain commonly leverage a fusion technique of various ensemble ways to much better take care of the learner's selection boundary, reduced samples, and ambiguous class problems that regular machine learning strategy are likely to own issue resolving.[four][9] Even so, th