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Network fault management aims to detect, identify and correct error conditions occurring in the network, providing users with reliable and stable network services. Recently, the utilization of machine learning methods for network fault management has attracted widespread attention. In this regard, this paper first introduced the research background of cell network fault management and explain the process and function of network fault management, and then introduced the existing cell network fault management frameworks. Subsequently, this paper reviewed the existing research on machine learning methods in cell network fault management. Referring to the fault management lifecycle, this paper introduced, summarized and compared the machine learning methods for fault detection, fault diagnosis and fault prediction for the purpose of providing reference for research in related fields. [ABSTRACT FROM AUTHOR]