基地研究员胡淑兰教授与合作者（Zhiyong Qian, School of Statistics and Mathematics, Zhongnan University of Economics and Law; Wangsen Xiao,  School of Statistics and Mathematics, Zhongnan University of Economics and Law）的论文 "The generalization ability of logistic regression with Markov sampling" 在重要学术期刊Electronic Research Archive在线发表。

  Abstract:

       In the case of non-independent and identically distributed samples, we propose a new ueMC algorithm based on uniformly ergodic Markov samples, and study the generalization ability, the learning rate and convergence of the algorithm. We develop the ueMC algorithm to generate samples from given datasets, and present the numerical results for benchmark datasets. The numerical simulation shows that the logistic regression model with Markov sampling has better generalization ability on large training samples, and its performance is also better than that of classical machine learning algorithms, such as random forest and Adaboost.

    Keywords：non-independent identically distributed samples, logistic regression model, uniformly ergodic Markov chain algorithm, generalization ability

 链接：http://www.aimspress.com/article/doi/10.3934/era.2023267

教师简介

 胡淑兰，中南财经政法大学统计与数学学院教授，博士生导师，文澜青年学者，青年教师“科研新星”。中国现场统计学会资源与环境分会理事，大数据分会理事和湖北省现场统计学会理事。主要从事大数据统计算法理论及其应用、经济计量方法及金融应用等方面的研究。在 《Bernoulli》《Statistics Sinica》《Stochastic Processes and their applications》《Science in China》《中国科学》等国内外权威学术期刊发表论文二十余篇，独撰学术专著1本，主编“十四五”全国统计规划教材《经济计量学》。主持并完成国家自然科学基金青年项目、国家社会科学基金一般项目、中央高校课题、研究生精品课程建设、全英文课程建设项目、企事业单位横向课题等十几项。荣获全国市场调查大赛、全国统计案例大赛、全国工业与经济金融大数据建模与计算大赛、美国数学建模大赛等各类比赛一二等指导学生奖。