Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, and defense, to name a few. The first comprehensive look at this new branch of machine learning, this volume offers a critical review of the problem of imbalanced learning, covering the state-of-the-art in techniques, principles, and real-world applications. Scientists and engineers will learn how to tackle the problem of learning from imbalanced datasets, and gain insight into current developments in the field as well as future research direction.
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算是一個論文集吧,居然有Balanced RF的性能評測,在論文裏都沒有找到
评分算是一個論文集吧,居然有Balanced RF的性能評測,在論文裏都沒有找到
评分算是一個論文集吧,居然有Balanced RF的性能評測,在論文裏都沒有找到
评分算是一個論文集吧,居然有Balanced RF的性能評測,在論文裏都沒有找到
评分算是一個論文集吧,居然有Balanced RF的性能評測,在論文裏都沒有找到
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