Boosting:Foundations and Algorithms. Schapire R E,Freund Y. . 2013Robert, E., Freund, Y.: Boosting - Foundations and Algorithms. MIT Press (2012)Robert E. Schapire and Yoav Freund. Boosting: Foundations and Al- gorithms. The MIT Press, 2012.Schapire, Robert E. and Freund, Yoav. ...
副标题: Foundations and Algorithms出版年: 2012-5-18页数: 544定价: USD 57.00装帧: Hardcover丛书: Adaptive Computation and Machine LearningISBN: 9780262017183豆瓣评分 9.2 14人评价 5星 57.1% 4星 35.7% 3星 7.1% 2星 0.0% 1星 0.0% 评价:
Title: Boosting: Foundations and Algorithms Author(s) Robert E. Schapire, Yoav Freund Publisher: The MIT Press (January 10, 2014) License(s): MIT Open Access License Paperback: 544 pages eBook: HTML and PDF Language: English ISBN-10: 0262526034 ISBN-13: 978-0262526036 Share This: ...
《Computing reviews》|2013年第3期|157-157|共1页 作者 George Hacken; 作者单位 收录信息 原文格式PDF 正文语种eng 中图分类 关键词 ALGORITHMS;DESIGN;EXPERIMENTATION;MEASUREMENT;PERFORMANCE;THEORY; 机译:算法;设计;实验;测量;性能;理论; 入库时间2022-08-17 13:38:13...
[2] Schapire R E, Freund Y.Boosting: Foundations and algorithms[M]. MIT press, 2012. [3] Breiman L. Stackedregressions[J]. Machine learning, 1996, 24(1): 49-64. 想关注更多有趣的机器学习/计算物理/医疗影像的科普/前沿研究,请关注我们的公众号 ...
不知道用来训练普通深度模型效果会怎样,竞争 layer-wise pretraining 现在已经显得有点过时了。 References Schapire & Freund. Boosting: Foundations and Algorithms. MIT. He et al.Deep Residual Learning for Image Recognition. Veit et al.Residual Networks Behave Like Ensembles of Relatively Shallow Networks....
Schapire & Freund. Boosting: Foundations and Algorithms. MIT. He et al.Deep Residual Learning for Image Recognition. Veit et al.Residual Networks Behave Like Ensembles of Relatively Shallow Networks. Xie et al.Aggregated Residual Transformations for Deep Neural Networks....
我想掌握这些结论(或者常识)是不够,还需要知道Why,因此在结合西瓜书和《Ensemble Mothods: Foundations and Algorithms》以及FHT00(ADDITIVE LOGISTIC REGRESSION: A STATISTICAL VIEW OF BOOSTING)资料之后,发现对于AdaBoost的研究与解释,如AdaBoost能够对抗过拟合问题(不断加大基模型个数,在测试集上范化误差居然可以一直...
(2012). Boosting: Foundations and algorithms. Cambridge: MIT Press. Google Scholar Schapire, R. E., & Singer, Y. (1999). Improved boosting algorithms using confidence-rated predictions. Machine learning, 37(3), 297–336. Article MATH Google Scholar Schölkopf, B., & Smola, A. J. (...
推荐南京大学周志华老师的一篇综述文章:Ensemble methods: foundations and algorithms 里面对各种ensemble模型的原理、优缺点都有很好的分析,如果想读原始论文,可以看每一章后面further readings里面提到的文章。 有用2 回复 撰写回答 你尚未登录,登录后可以 和开发者交流问题的细节 关注并接收问题和回答的更新提醒 参与...