The key of a good ensemble learning algorithm is able to generate the diversity of individual learners.
一个好的集成学习算法，关键是能生成差异度大的个体分类器。
Ensemble learning is a research hotspot in machine learning, which can improve generalization performance of classification algorithm.
集成学习是当前机器学习的一个研究热点，它可以提高分类算法的泛化性能。
So it has become an important research topic of ensemble learning. A better selection strategy and improvement of the speed of algorithm need more researches.
因此选择性集成已成为集成学习的一个重要研究方向，其更好的选择策略以及算法运算速度的提高有待更多研究人员的深入研究。
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