How to Apply Multithreading to Improve the Efficiency of Backward Elimination in Linear Regression

论文摘要

Backward elimination is a very important technique for finding the important factors in a linear regression model.However,the traditional backward elimination can be slow when the dataset is extremely large.Therefore,trying to use multithreading to improve the performance of backward elimination and approximate the original result is helpful.

论文目录

文章来源

类型: 国际会议

作者: Yiyang Zeng

来源: 2019 IERI International Conference on Economics,Management,Applied Sciences and Social Science(EMAS 2019) 2019-01-03

年度: 2019

分类: 基础科学

专业: 数学

单位: New York University

分类号: O212.1

DOI: 10.26914/c.cnkihy.2019.053244

页码: 417-420

总页数: 4

文件大小: 399k

下载量: 1

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