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Optimal Representative Sample Weighting
- Source :
- SSRN Electronic Journal.
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- We consider the problem of assigning weights to a set of samples or data records, with the goal of achieving a representative weighting, which happens when certain sample averages of the data are close to prescribed values. We frame the problem of finding representative sample weights as an optimization problem, which in many cases is convex and can be efficiently solved. Our formulation includes as a special case the selection of a fixed number of the samples, with equal weights, i.e., the problem of selecting a smaller representative subset of the samples. While this problem is combinatorial and not convex, heuristic methods based on convex optimization seem to perform very well. We describe rsw, an open-source implementation of the ideas described in this paper, and apply it to a skewed sample of the CDC BRFSS dataset.
- Subjects :
- FOS: Computer and information sciences
Statistics and Probability
Computer Science - Machine Learning
Mathematical optimization
Optimization problem
Iterative proportional fitting
Computer science
Heuristic (computer science)
Frame (networking)
Machine Learning (stat.ML)
Sample (statistics)
Machine Learning (cs.LG)
Theoretical Computer Science
Weighting
Methodology (stat.ME)
Set (abstract data type)
Computational Theory and Mathematics
Statistics - Machine Learning
Optimization and Control (math.OC)
Convex optimization
FOS: Mathematics
Statistics, Probability and Uncertainty
Special case
Mathematics - Optimization and Control
Statistics - Methodology
Subjects
Details
- ISSN :
- 15565068
- Database :
- OpenAIRE
- Journal :
- SSRN Electronic Journal
- Accession number :
- edsair.doi.dedup.....e66ee77952740513a777bc864a2f9e6f