Suppose you are given a set of $25$ classifiers that all model a simple binary classification problem. You do some experiments all these classifiers with the validation data, and you find that the most accurate classifier has an accuracy of $0\mathrm{.}47.$ Would this set of classifiers be a good set from which to build an ensemble classifier that uses these classifiers as base classifiers? Why or why not?