How Feature Remove and Shuffle Work in Key Feature Detection? The Perspective of NDER

Xingyu Xu,Ding Tan,Sihai Zhang,Tianchi Chen

2021 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)（2021）

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摘要

In the classification scenario, the key feature detection (KFD) aims to locate the features that have a decisive impact on different real labels in the dataset. Commonly used KFD methods are usually based on feature selection framework, including three categories: filter, wrapper and embedded. Among them, the wrapper-type KFD methods usually remove one feature or shuffle the value of one feature f...

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关键词

Error analysis,Feature detection,Simulation,Rough sets,Big Data,Feature extraction,Filtering theory

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