重庆科技大学学报（自然科学版）2024，Vol.26Issue(6)：59-64,6.DOI:10.19406/j.issn.2097-4531.2024.06.009
一种高效的回归参数估计数值方法
An Efficient Numerical Method for Estimating Regression Parameters
摘要
Abstract
In the study of linear regression parameter estimation,traditional gradient descent and Newton's method are often limited by local convergence issues and are highly sensitive to the choice of initial values and learning rates.To overcome these limitations,a regression parameter estimation algorithm based on central difference is pro-posed,which uses central differences to approximate the partial derivatives of the loss function,effectively reducing the model's dependence on learning rate adjustment and initial value selection.The experimental results of the line-ar regression model of children's urine creatinine content and age show that the algorithm has significant advantages in terms of computational efficiency and initial value sensitivity,which can greatly improve convergence speed and accuracy.The goodness of fit and mean square error of the algorithm are very close to the least squares method,demonstrating excellent robustness and wide applicability.关键词
线性回归/参数估计/中心差商/牛顿法Key words
linear regression/parameter estimation/central difference/Newton's method分类
信息技术与安全科学引用本文复制引用
余婉风..一种高效的回归参数估计数值方法[J].重庆科技大学学报（自然科学版）,2024,26(6):59-64,6.基金项目
2022年安徽省科研编制计划项目"数字化转型背景下北斗技术在水利工程监测中的应用研究"(2022AH030159) （2022AH030159）
2023年安徽省教育厅高校自然科学基金重点项目"基于北斗/多源传感器数据融合的实时滑坡预警智能系统研究"(2023AH052920) （2023AH052920）
