Customised-sampling approach for pipe failure prediction in water distribution networks
Milad Latifi,
Ramiz Beig Zali,
Akbar A. Javadi
et al.
Abstract:This paper presents a new methodology for addressing imbalanced class data for failure prediction in Water Distribution Networks (WDNs). The proposed methodology relies on existing approaches including under-sampling, over-sampling, and class weighting as primary strategies. These techniques aim to treat the imbalanced datasets by adjusting the representation of minority and majority classes. Under-sampling reduces data in the majority class, over-sampling adds data to the minority class, and class weighting a… Show more
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