This paper proposes a text classification method based on Cloud Theory and neural network structure decision tree.

提出一种基于云理论和神经网络构造决策树的文本分类方法。

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Empirical results show that genetic programming model is more advantageous than traditional statistical models, neural network models and decision tree models in prediction accuracy and robustness.

检验结果表明，该模型在预测精度、实用价值和鲁棒性方面都优于传统的统计模型、神经网络模型和决策树模型。

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It adopts cloud neural network to study the cloud mapping relationship between variables, so as to generate cloud decision tree.

运用云神经网络学习变量间的云映射关系，从中生成云决策树。

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