Model loss and distribution analysis of regression problems in machine learning
文献类型:会议论文
作者 | Wang TR(王天然)1,2,3; Yang N(杨楠)1,2,3; Zheng ZY(郑泽宇)1,2,3 |
出版日期 | 2019 |
会议日期 | February 22-24, 2019 |
会议地点 | Zhuhai, China |
关键词 | Statistics machine learning regression model maximum likelihood |
页码 | 1-5 |
英文摘要 | The machine learning regression model is based on the assumption of normal distribution. In this paper, we mainly study the probability distribution of the machine learning model and the effect of the convergence values of different loss functions on the probability distribution model. Based on the idea of robust regression and the assumption of homogeneous variance of the model, we solved the statistical solution of two-dimensional regression problem by using least square method. The maximum likelihood estimation parameters of the probabilistic model are obtained by using the maximum likelihood estimation method. In order to compare the solving parameters of the two methods, the convergence values of L1 loss function and L2 loss function are used for the regression verification. Through the mathematical and statistical rigorous derivation, obtained two important conclusions; First, under the condition that the data satisfies normal distribution and is based on the assumption of homogeneous variance, the probability model conforms to the multivariate gaussian distribution. Secondly, the model satisfying the multi-gaussian distribution has little influence on the parameter estimation under the condition of the large number theorem, that is, the multi-gaussian distribution model has good tolerance to the loss function. © 2019 Association for Computing Machinery. |
源文献作者 | Asia Society of Researchers ; Metropolitan State University of Denver ; Southwest Jiaotong University ; University of Macau |
产权排序 | 1 |
会议录 | ACM International Conference Proceeding Series |
会议录出版者 | ACM |
会议录出版地 | New York |
语种 | 英语 |
ISBN号 | 978-1-4503-6600-7 |
源URL | [http://ir.sia.cn/handle/173321/24686] |
专题 | 沈阳自动化研究所_数字工厂研究室 |
通讯作者 | Yang N(杨楠) |
作者单位 | 1.University of Chinese Academy of Sciences, Beijing 1000049, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
推荐引用方式 GB/T 7714 | Wang TR,Yang N,Zheng ZY. Model loss and distribution analysis of regression problems in machine learning[C]. 见:. Zhuhai, China. February 22-24, 2019. |
入库方式: OAI收割
来源:沈阳自动化研究所
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