圖書標籤: 機器學習 boosting MachineLearning 統計學習 模式識彆 計算機 泛化誤差 數據挖掘
发表于2024-11-26
Boosting pdf epub mobi txt 電子書 下載 2024
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.
書寫的比較基礎,以boosting入手來分析,順道寫瞭幾章個人認為冗餘的理論 ps要不是寫作業要看,我估計真不會仔細看
評分boosting講得跟係統,不可否認的是實用性較差,雖然也有僞代碼,但誤差分析占瞭大部分內容,五星給第二部分,把boosting和game theory, svm, lr都結閤起來瞭,有點兒數學美感的意思
評分書寫的比較基礎,以boosting入手來分析,順道寫瞭幾章個人認為冗餘的理論 ps要不是寫作業要看,我估計真不會仔細看
評分書寫的比較基礎,以boosting入手來分析,順道寫瞭幾章個人認為冗餘的理論 ps要不是寫作業要看,我估計真不會仔細看
評分書寫的比較基礎,以boosting入手來分析,順道寫瞭幾章個人認為冗餘的理論 ps要不是寫作業要看,我估計真不會仔細看
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...
評分和侧重广度的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...
評分和侧重广度的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...
評分和侧重广度的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...
評分和侧重广度的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 pdf epub mobi txt 電子書 下載 2024