为了证明算法的有效性，采用决策树作为基分类器。

In order to prove the validity of the algorithm, it USES decision tree as the base learner.

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采用基于灵敏度分析的BP神经网络模型作为基分类器，进一步剔除冗余基因。

BP neural network based on sensitivity analysis is used as base classifier to learn the subsets and redundant genes are further removed.

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本文还以SURPASS为基分类器实现了随机森林，最后通过实验验证了随机森林的性质。

Also, this paper build a random forest based on SURPASS and verifies the character of random forest by doing some experiments.

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