| 期刊全稱 | An Introduction to Statistical Learning | | 期刊簡(jiǎn)稱 | with Applications in | | 影響因子2023 | Gareth James,Daniela Witten,Jonathan Taylor | | 視頻video | http://file.papertrans.cn/156/155491/155491.mp4 | | 發(fā)行地址 | Presents an essential statistical learning toolkit for practitioners in science, industry, and other fields.Demonstrates application of the statistical learning methods in Python.Covers regression, cl | | 學(xué)科分類(lèi) | Springer Texts in Statistics | | 圖書(shū)封面 |  | | 影響因子 | .An Introduction to Statistical Learning.?provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and? astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. . .Four of the authors co-wrote?.An Introduction to Statistical Learning, With Applications in R.(ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing th | | Pindex | Textbook 2023 |
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