An Optimization Approach of Deriving Bounds between Entropy and Error from Joint Distribution: Case Study for Binary Classifications
文献类型：期刊论文
| 作者 | Hu, Bao-Gang1 ; Xing, Hong-Jie2
|
| 刊名 | ENTROPY
 |
| 出版日期 | 2016-02-01 |
| 卷号 | 18期号:2页码:1-19 |
| 关键词 | Entropy Error Probability Bayesian Errors Error Types Upper Bound Lower Bound |
| DOI | 10.3390/e18020059 |
| 文献子类 | Article |
| 英文摘要 | In this work, we propose a new approach of deriving the bounds between entropy and error from a joint distribution through an optimization means. The specific case study is given on binary classifications. Two basic types of classification errors are investigated, namely, the Bayesian and non-Bayesian errors. The consideration of non-Bayesian errors is due to the facts that most classifiers result in non-Bayesian solutions. For both types of errors, we derive the closed-form relations between each bound and error components. When Fano's lower bound in a diagram of Error Probability vs. Conditional Entropy is realized based on the approach, its interpretations are enlarged by including non-Bayesian errors and the two situations along with independent properties of the variables. A new upper bound for the Bayesian error is derived with respect to the minimum prior probability, which is generally tighter than Kovalevskij's upper bound. |
| WOS关键词 | PATTERN-RECOGNITION ; FEATURE-SELECTION ; PROBABILITY ; INFORMATION ; INEQUALITIES ; DECISIONS ; CRITERIA |
| WOS研究方向 | Physics |
| 语种 | 英语 |
| WOS记录号 | WOS:000371827800018 |
| 资助机构 | National Natural Science Foundation of China(61273196 ; 61573348 ; 60903089) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/11372]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, NLPR LIAMA, Beijing 100190, Peoples R China 2.Hebei Univ, Coll Math & Informat Sci, Baoding 071002, Peoples R China |
| 推荐引用方式 GB/T 7714 | Hu, Bao-Gang,Xing, Hong-Jie. An Optimization Approach of Deriving Bounds between Entropy and Error from Joint Distribution: Case Study for Binary Classifications[J]. ENTROPY,2016,18(2):1-19. |
| APA | Hu, Bao-Gang,&Xing, Hong-Jie.(2016).An Optimization Approach of Deriving Bounds between Entropy and Error from Joint Distribution: Case Study for Binary Classifications.ENTROPY,18(2),1-19. |
| MLA | Hu, Bao-Gang,et al."An Optimization Approach of Deriving Bounds between Entropy and Error from Joint Distribution: Case Study for Binary Classifications".ENTROPY 18.2(2016):1-19. |
入库方式： OAI收割
来源：自动化研究所
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