Liu regression after random forest for prediction and modeling in high dimension-Reference-Cited by-同舟云学术

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Liu regression after random forest for prediction and modeling in high dimension

Published:2022-03-10 Issue:4 Volume:36 Page:
ISSN:0886-9383
Container-title:Journal of Chemometrics
language:en
Short-container-title:Journal of Chemometrics

Author:

Arashi Mohammad¹,Lukman Adewale F.²^ORCID,Algamal Zakariya Y.³^ORCID

Affiliation:

1. Department of Statistics, Faculty of Mathematical Sciences Ferdowsi University of Mashhad Mashhad Iran

2. Department of Epidemiology and Biostatistics University of Medical Sciences Ondo Nigeria

3. Department of Statistics and Informatics University of Mosul Mosul Iraq

Funder

Ferdowsi University of Mashhad

Publisher

Wiley

Subject

Applied Mathematics,Analytical Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cem.3393

Reference31 articles.

1. Unsupervised random forest: a tutorial with case studies

2. A Systematic Approach for Variable Selection With Random Forests: Achieving Stable Variable Importance Values

3. Correlation and redundancy on machine learning performance for chemical databases

4. A comparison of random forest variable selection methods for classification prediction modeling

5. Different strategies for the use of random forest in NMR spectra

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