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A dynamic programming approach to segmented isotonic regression

Víctor Bucarey 1 Martine Labbé 2, 3 Juan Morales 4, * Salvador Pineda 5
* Corresponding author
1 Data Analytics Laboratory
2 INOCS - Integrated Optimization with Complex Structure
ULB - Université libre de Bruxelles, Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
3 Département d'informatique [Bruxelles]
4 Department of Applied Mathematics
5 Department of Electrical Engineering
Abstract : This paper proposes a polynomial-time algorithm to construct the monotone stepwise curve that minimizes the sum of squared errors with respect to a given cloud of data points. The fitted curve is also constrained on the maximum number of steps it can be composed of and on the minimum step length.
Keywords : Cardinality-constrained shortest path problem isotonic regression segmented regression inverse optimization data clustering consumers' price-response
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Preprints, Working Papers, ...
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https://hal.inria.fr/hal-03046338
Contributor : Martine Labbé <>
Submitted on : Tuesday, December 8, 2020 - 1:27:43 PM
Last modification on : Thursday, January 21, 2021 - 1:22:18 PM

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Víctor Bucarey, Martine Labbé, Juan Morales, Salvador Pineda. A dynamic programming approach to segmented isotonic regression. 2020. ⟨hal-03046338⟩

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