Variable Selection based on a Two-stage Projection Pursuit Algorithm

Shu Jiang, Yijun Xie

Abstract

Dimension reduction methods have gained popularity in modern era due to exponential growth in data collection. Extracting key information and learning from all available data is a crucial step. Principal component analysis (PCA) is a popular dimension reduction technique due to its simplicity and flexibility. We stress that PCA is solely based on maximizing the proportion of total variance of the explanatory variables and do not directly impact the outcome of interest. Variable selection under such unsupervised setting may thus be inefficient. In this note, we propose a novel two-stage projection pursuit based algorithm which simultaneously consider the loss in the outcome variable when doing variable selection. We believe that when one is keen in variable selection in relation to the outcome of interest, the proposed method may be more efficient compared to existing methods.

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Paper Citation


in Harvard Style

Jiang S. and Xie Y. (2020). Variable Selection based on a Two-stage Projection Pursuit Algorithm.In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, ISBN 978-989-758-398-8, pages 188-193. DOI: 10.5220/0009098901880193


in Bibtex Style

@conference{bioinformatics20,
author={Shu Jiang and Yijun Xie},
title={Variable Selection based on a Two-stage Projection Pursuit Algorithm},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS,},
year={2020},
pages={188-193},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009098901880193},
isbn={978-989-758-398-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS,
TI - Variable Selection based on a Two-stage Projection Pursuit Algorithm
SN - 978-989-758-398-8
AU - Jiang S.
AU - Xie Y.
PY - 2020
SP - 188
EP - 193
DO - 10.5220/0009098901880193