..._矫正 关键词:虚点;分类算法;特征权重;向量空间模型 [gap=1658]Keywords: Virtual point, text categorization, feature weight, vector space model ...
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The experiments indicate that considering feature weight is rational and necessary.
最后的实验也表明了考虑特征权重的合理性和必要性。
参考来源 - 符号聚类新方法的研究及应用This paper discusses the application of Vector Space Model(VSM) in Text Categorization and analyses the traditional algorithm of term weighting: TF-IDF.
该文首先讨论了向量空间模型在文本分类中的应用,并且对传统特征权重算法TF-IDF进行了分析。
参考来源 - 基于向量空间模型的文本分类特征权重算法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
文章研究并改进了文本自动分类中的特征权重算法。
This article aims to improve the algorithm of term weighting in automated text classification.
相关反馈方法有许多种，如移动查询向量、修改特征权重、贝叶斯、支持向量、神经网络等。
Such as move query vector, modify the weight of characteristics, Bayesian, SVM, neural and networks.
特征权重学习是基于特征赋权的K近邻算法需要解决的重要问题之一，传统上提出了许多启发式的学习方法。
Feature weighting is one of the important problems for feature weighting based KNN algorithm, and many heuristic methods have been employed to solve the problem traditionally.
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