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- W2182726434 abstract "Selective ensemble learning is a method that selects a subset of diverse and accurate base models to generate stronger generalization ability. In this paper, we propose a selective ensemble learning algorithm called PTHS and a novel feature selection method called MSRD to solve the problem of high dimensionality. The algorithm PTHS uses a parallel optimization and hierarchical selection framework. The experimental result showed that MSRD is a suitable feature selection method for solving the problem of high dimensionality and that PTHS achieved better performance than other methods." @default.
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- W2182726434 date "2015-07-01" @default.
- W2182726434 modified "2023-09-27" @default.
- W2182726434 title "Selective ensemble learning with parallel optimization and hierarchical selection" @default.
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- W2182726434 doi "https://doi.org/10.1109/icmlc.2015.7340921" @default.
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