苏州科技大学学报（自然科学版）2018，Vol.35Issue(2)：26-31,6.DOI:10.12084/j.issn.2096-3289.2018.02.006
梯度下降法在机器学习中的应用
Application of gradient descent method in machine learning
摘要
Abstract
In order to solve the problem of machine learning training algorithm ,the author discussed the basic iterative steps of gradient descent method and its variant algorithm. The gradient descent method was used to minimize the cost function. Based on the implementation of MATLAB program ,linear regression model and logistic regression classification model were analyzed. By comparing the convergence speed and complexity of the algorithm,the author obtained the application examples of different models. The result shows that choosing the better optimization algorithm according to the different data sets can make work faster.关键词
梯度下降法/线性回归/逻辑回归/MATLABKey words
gradient descent method/linear regression/logistic regression/MATLAB分类
数理科学引用本文复制引用
孙娅楠,林文斌..梯度下降法在机器学习中的应用[J].苏州科技大学学报（自然科学版）,2018,35(2):26-31,6.基金项目
国家自然科学基金资助项目(11547311) （11547311）
