混淆矩阵
混乱
构造(python库)
班级(哲学)
基质(化学分析)
计算机科学
人工智能
过程(计算)
数学
机器学习
算法
数据挖掘
心理学
材料科学
精神分析
复合材料
程序设计语言
操作系统
作者
Xinyang Deng,Qi Liu,Yong Deng,Sankaran Mahadevan
标识
DOI:10.1016/j.ins.2016.01.033
摘要
The determination of basic probability assignment (BPA) is a crucial issue in the application of Dempster–Shafer evidence theory. Classification is a process of determining the class label that a sample belongs to. In classification problem, the construction of BPA based on the confusion matrix has been studied. However, the existing methods do not make full use of the available information provided by the confusion matrix. In this paper, an improved method to construct the BPA is proposed based on the confusion matrix. The proposed method takes into account both the precision rate and the recall rate of each class. An illustrative case regarding the prediction of transmembrane protein topology is given to demonstrate the effectiveness of the proposed method.
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