首页> 外文会议>Algorithmic learning theory >Analysis of Case-Based Representability of Boolean Functions by Monotone Theory
【24h】

Analysis of Case-Based Representability of Boolean Functions by Monotone Theory

机译:基于个案的布尔函数基于个案的可表示性分析

获取原文
获取原文并翻译 | 示例

摘要

Classification is one of major tasks in case-based reasoning (CBR) and many studies have been done for analyzing properties of case-based classification (1,14,10,15,12,9,13,7]. However, these studies only consider numerical similarity measures whereas there are other kind of similarity measure for differnet tasks. Among these measures, HYPO system [2,3] in a legal domain uses a similarity measure based on set inclusion of differences of attributes in cases.
机译:分类是基于案例的推理(CBR)的主要任务之一,并且已经进行了许多研究来分析基于案例的分类的属性(1,14,10,15,12,9,13,7]。仅考虑数值相似性度量,而针对差异网络任务还有其他类型的相似性度量,在这些度量中,法律领域的HYPO系统[2,3]使用基于案例中属性差异集的相似性度量。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号