1) characters classification weight
分类特征权重
2) weighted feature classification
特征加权分类
1.
In view of the discovery that the different network data features have different influence on classification results in SVM-based network intrusion detection,a new SVM weighted feature classification method is brought forward in order to get optimal classification plane.
在SVM的网络入侵检测中,发现不同的网络数据特征对分类结果的影响程度不同,针对这一问题,提出了一种新型SVM特征加权分类方法,以获得更好的最优分类面。
3) term-weighting
特征权重分析
4) feature weighting
特征权重
1.
Performance of feature weighting computation directly influences precision of text classification or clustering.
特征权重计算是文本表示的关键,权重计算方法的优劣直接影响文本分类和聚类的准确度。
5) Feature weight
特征权重
1.
A topic-based feature weight calculation method for patent categorization
专利分类中基于主题的特征权重计算方法
2.
After feature reduction,based on the hypothesis that time factor has a significant affect on the adoptability of the history cases,a small scale algorithm for case feature weight calculation called TSBMPSA is proposed.
经过特征约简,在假设时间因素对历史案例可采纳程度有显著影响基础上,提出了一种小规模的基于时序的案例特征权重多阶段调整算法。
3.
This paper mainly discusses the feature weight autolearning method for casebased reasoning.
重点讨论了基于案例推理中特征权重的自动学习方法。
补充资料：因侵害姓名权、肖像权、名誉权、荣誉权产生的索赔权
因侵害姓名权、肖像权、名誉权、荣誉权产生的索赔权：公民、法人的姓名权、名称权，名誉权、荣誉权、受到侵害的有权要求停止侵害，恢复名誉，消除影响，赔礼道歉，并可以要求赔偿损失。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条