Model Loss and Distribution Analysis of Regression Problems in Machine Learning-Reference-Cited by-同舟云学术

Model Loss and Distribution Analysis of Regression Problems in Machine Learning

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 11th International Conference on Machine Learning and Computing - ICMLC '19
language:
Short-container-title:

Author:

Yang Nan¹,Zheng Zeyu¹,Wang Tianran¹

Affiliation:

1. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China and Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China and University of Chinese Academy of Sciences, Beijing, China

Publisher

ACM Press

Reference27 articles.

1. Feifei L, Fergus R, Perona P. Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories[J]. Computer Vision \& Image Understanding, 2005, 106(1):59--70. Ding, W. and Marchionini, G. 1997. A Study on Video Browsing Strategies. Technical Report. University of Maryland at College Park.

2. Kim B, Rudin C, Shah J. The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification[J]. Advances in Neural Information Processing Systems, 2014, 3:1952--1960.

3. Parsons S, Jones G. Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural Networks[J]. Journal of Experimental Biology, 2000, 203(17):2641--56.

4. Wu D, Fu X, Wen Y, et al. High-resolution melting combines with Bayes discriminant analysis: a novel hepatitis C virus genotyping method.[J]. Clinical \& Experimental Medicine, 2017, 17(3):1--8.

5. Jagerman D L. Some Properties of the Erlang Loss Function[J]. Bell Labs Technical Journal, 1974, 53(3):525--551.

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Remotely sensed estimates of long-term biochemical oxygen demand over Hong Kong marine waters using machine learning enhanced by imbalanced label optimisation;Science of The Total Environment;2024-09

2. Heart rate prediction with contactless active assisted living technology: a smart home approach for older adults;Frontiers in Artificial Intelligence;2024-01-12

3. Machine Learning Regressors in Forecasting Mechanical Properties in Advanced Manufacturing Processes;Lecture Notes in Networks and Systems;2024

4. Predicting aqueous sorption of organic pollutants on microplastics with machine learning;Water Research;2023-10

5. Robust water level measurement method based on computer vision;Journal of Hydrology;2023-05