Boosting 在线电子书 图书标签: 机器学习 boosting MachineLearning 统计学习 模式识别 计算机 泛化误差 数据挖掘
发表于2024-11-25
Boosting 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024
作为boosting的发明人,其实他自己也不是很懂boosting。
评分书写的比较基础,以boosting入手来分析,顺道写了几章个人认为冗余的理论 ps要不是写作业要看,我估计真不会仔细看
评分书写的比较基础,以boosting入手来分析,顺道写了几章个人认为冗余的理论 ps要不是写作业要看,我估计真不会仔细看
评分boosting讲得跟系统,不可否认的是实用性较差,虽然也有伪代码,但误差分析占了大部分内容,五星给第二部分,把boosting和game theory, svm, lr都结合起来了,有点儿数学美感的意思
评分书写的比较基础,以boosting入手来分析,顺道写了几章个人认为冗余的理论 ps要不是写作业要看,我估计真不会仔细看
Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate "rules of thumb." A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.
和侧重广度的prml不一样,本书通过adaboost算法及boosting这种思想,从纵向的角度像我们介绍了机器学习的方方面面,从泛化误差的推导到boosting与其他主流的算法的联系再到应用,作者以boosting为核心,对机器学习中的确定性算法给出了一个有深度的介绍。全书逻辑清晰,算法思...
评分和侧重广度的prml不一样,本书通过adaboost算法及boosting这种思想,从纵向的角度像我们介绍了机器学习的方方面面,从泛化误差的推导到boosting与其他主流的算法的联系再到应用,作者以boosting为核心,对机器学习中的确定性算法给出了一个有深度的介绍。全书逻辑清晰,算法思...
评分和侧重广度的prml不一样,本书通过adaboost算法及boosting这种思想,从纵向的角度像我们介绍了机器学习的方方面面,从泛化误差的推导到boosting与其他主流的算法的联系再到应用,作者以boosting为核心,对机器学习中的确定性算法给出了一个有深度的介绍。全书逻辑清晰,算法思...
评分和侧重广度的prml不一样,本书通过adaboost算法及boosting这种思想,从纵向的角度像我们介绍了机器学习的方方面面,从泛化误差的推导到boosting与其他主流的算法的联系再到应用,作者以boosting为核心,对机器学习中的确定性算法给出了一个有深度的介绍。全书逻辑清晰,算法思...
评分和侧重广度的prml不一样,本书通过adaboost算法及boosting这种思想,从纵向的角度像我们介绍了机器学习的方方面面,从泛化误差的推导到boosting与其他主流的算法的联系再到应用,作者以boosting为核心,对机器学习中的确定性算法给出了一个有深度的介绍。全书逻辑清晰,算法思...
Boosting 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024