Random forests regression for soft interval data-Reference-Cited by-同舟云学术

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Random forests regression for soft interval data

Published:2024-09-10 Issue: Volume: Page:1-20
ISSN:0361-0918
Container-title:Communications in Statistics - Simulation and Computation
language:en
Short-container-title:Communications in Statistics - Simulation and Computation

Author:

Gaona-Partida Paul¹,Yeh Chih-Ching²,Sun Yan³,Cutler Adele³

Affiliation:

1. Department of Statistics, University of California Irvine, Irvine, California, USA

2. Pharmaceutical & Life Sciences Research and Development, PricewaterhouseCoopers LLP, Salt Lake City, Utah, USA

3. Department of Mathematics & Statistics, Utah State University, Logan, Utah, USA

Funder

Utah State University, Department of Mathematics and Statistics.

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610918.2024.2396401

Reference42 articles.

1. A strong law of large numbers for random compact sets;Artstein Z.;Annals of Probability,1975

2. Integrals of set-valued functions

3. Billard L. 2007. Dependencies and variation components of symbolic interval-valued data. In Selected contributions in data analysis and classification ed. by Brito P. Cucumel G. Bertrand P. and Carvalho F. 3–12. Berlin: Springer.

4. Billard, L., and E. Diday. 2002. Symbolic regression analysis. Classification, Clustering and Data Analysis: Proceedings of the Eighth Conference of the International Federation of Classification Societies (IFCS’02) Springer, Poland, pp. 281–288.

5. Estimation of a flexible simple linear model for interval data based on set arithmetic

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