Comparison of classification accuracy using Cohen's Weighted Kappa
Comparison of classification accuracy using Cohen's Weighted Kappa
复制标题
DOI：
10.1016/j.eswa.2006.10.022
复制
发表时间：
2008-02-01
影响因子：
8.5
通讯作者：
Ben-David, Arie
中科院分区：
文献类型：
--
作者：
Ben-David, Arie
许多专家系统解决分类问题。在比较这类分类器的精确度时，必须经常考虑错误的代价。在这种对成本敏感的应用中，仅仅使用未命中百分比作为唯一的准确度指标可能会产生误导。这类问题的典型例子是医疗和军事应用，以及具有有序(即，有序)类的数据集。所采取的方法是基于科恩的卡帕统计量。它补偿了可能是由于偶然而进行的分类。建议使用Kappa作为衡量所有多值分类问题的精度的标准仪表。加权Kappa的使用使得能够有效地处理对成本敏感的分类。当误差代价未知且只能粗略估计时，强烈建议使用加权Kappa的灵敏度分析。(C)2006爱思唯尔有限公司。保留所有权利。
Many expert systems solve classification problems. While comparing the accuracy of such classifiers, the cost of error must frequently be taken into account. In such cost-sensitive applications just using the percentage of misses as the sole meter for accuracy can be misleading. Typical examples of such problems are medical and military applications, as well as data sets with ordinal (i.e., ordered) class.A new methodology is proposed here for assessing classifiers accuracy. The approach taken is based on Cohen's Kappa statistic. It compensates for classifications that may be due to chance. The use of Kappa is proposed as a standard meter for measuring the accuracy of all multi-valued classification problems. The use of Weighted Kappa enables to effectively deal with cost-sensitive classification. When the cost of error is unknown and can only be roughly estimated, the use of sensitivity analysis with Weighted Kappa is highly recommended. (c) 2006 Elsevier Ltd. All rights reserved.