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Consistent regression of biophysical parameters with kernel methods
- Publication Year :
- 2020
-
Abstract
- This paper introduces a novel statistical regression framework that allows the incorporation of consistency constraints. A linear and nonlinear (kernel-based) formulation are introduced, and both imply closed-form analytical solutions. The models exploit all the information from a set of drivers while being maximally independent of a set of auxiliary, protected variables. We successfully illustrate the performance in the estimation of chlorophyll content.<br />Comment: arXiv admin note: substantial text overlap with arXiv:1710.05578
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2012.04922
- Document Type :
- Working Paper