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Improvement and Implementation of Feature Weighting Algorithm TF-IDF in Text Classification

机译:文本分类中特征加权算法TF-IDF的改进与实现

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摘要

Based on the introduction of the traditional feature weighting algorithm TF-IDF, based on the phenomenon that the eigenvalue extraction is not effective when the text to be classified is not uniform, an improved TF-IDF algorithm is proposed in this paper, which considers the uneven text distribution Inside. The experimental results show that the results obtained by the classification algorithm using the improved algorithm are better than the original algorithm in terms of accuracy and recall and make up for the defects of the original TF-IDF algorithm.
机译:基于传统特征加权算法TF-IDF的引入,基于特征值提取在待分类的文本不均匀的现象不均匀的现象,本文提出了一种改进的TF-IDF算法,其考虑了内部文本分发不均匀。实验结果表明,通过使用改进的算法的分类算法获得的结果优于准确度和召回的原始算法,并弥补原始TF-IDF算法的缺陷。

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