Analysis and Mitigation of Unwanted Biases in ML-based QoT Classification Tasks

被引：0

作者：

Natalino, Carlos ^{[1
]}

Shariati, Behnam ^{[2
]}

Safari, Pooyan ^{[2
]}

Fischer, Johannes Karl ^{[2
]}

Monti, Paolo ^{[1
]}

机构：

[1] Chalmers Univ Technol, Dept Elect Engn, S-41296 Gothenburg, Sweden

[2] Fraunhofer HHI, D-10587 Berlin, Germany

来源：

2024 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXHIBITION, OFC | 2024年

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We address the problem of mitigating biases in models used for the quality of transmission prediction. The proposed method reduces the relative accuracy difference between samples with different feature values by up to 45%. (c) 2024 The Author(s)

引用

页数：3

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