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• W3117542617 abstract "Piecewise linear regression is a powerful and flexible regression technique where the dataset is divided into disjoint partitions and a separate regression is computed for each partition. Here, we consider the piecewise linear regression problem where the data partitioning is performed via a fixed number of break points on a predetermined dimension. We develop a column generation heuristic based on a set partitioning formulation of the problem and evaluate its prediction performance using a mixed integer programming formulation introduced earlier as a benchmark. Our results show that the proposed heuristic displays an efficient and robust performance, and also scales up smoothly as the dataset grows." @default.
• W3117542617 created "2021-01-05" @default.
• W3117542617 creator A5053671396 @default.
• W3117542617 creator A5084660580 @default.
• W3117542617 date "2021-06-01" @default.
• W3117542617 modified "2023-09-27" @default.
• W3117542617 title "A column generation based heuristic algorithm for piecewise linear regression" @default.
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• W3117542617 doi "https://doi.org/10.1016/j.eswa.2020.114539" @default.
• W3117542617 hasPublicationYear "2021" @default.
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