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Article Dans Une Revue International Journal of Approximate Reasoning Année : 2011

A Midpoint-Radius Approach to Regression with Interval Data

Résumé

In this paper, a revisited interval approach for linear regression is proposed. In this context, according to the Midpoint-Radius (MR) representation, the uncertainty attached to the setvalued model can be decoupled from its trend. The estimated interval model is built from interval input-output data with the objective of covering all available data. The constrained optimization problem is addressed using a linear programming approach in which a new criterion is proposed for representing the global uncertainty of the interval model. The potential of the proposed method is illustrated by simulation examples.

Dates et versions

hal-00633518 , version 1 (18-10-2011)

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Citer

Reda Boukezzoula, Sylvie Galichet, Amory Bisserier. A Midpoint-Radius Approach to Regression with Interval Data. International Journal of Approximate Reasoning, 2011, 52 (9), pp. 1257-1271. ⟨10.1016/j.ijar.2011.07.002⟩. ⟨hal-00633518⟩
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