Techniques such as Bayesian networks or neural networks use highly expressive models, which try to produce a non-biased classifier in order to "describe" a corpus of documents.

Bayesian网络或神经网络等技术使用表达能力非常强的模型，力求生成无偏向的分类器来“描述”文档集。

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A mix model with the subspace classifier and BP neural network classifier was realized, which is used in handwritten English letter and number recognition.

最后，用子空间分类器和BP神经网络分类器构造了一个混联模型，用于手写英文字母和数字的识别。

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This paper presents a multiclass neural network classifier to learn disjunctive fuzzy information in the feature space.

本篇论文提出一个类神经网路分类器来学习多类的分离模糊资讯。

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