Statistical Machine Learning:Error Analysis and 陈洪从泛化性能分析的角度系统阐述机器学习中三类问题(回归、排序、多分类)的理论基础、算法构建方法以及应用。学习理论基础方面重点关注算法的泛化性、稀疏性和稳定性分析,应用部分重点关注其在数据挖掘具体任务中的有效性和竞争性。全书分三章,即回归学习理论与应用、...
"Statistical Machine Learning" provides mathematical tools for analyzing the behavior and generalization performance of machine learning algorithms.
Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at ...
The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. This major new edition features many topics...
Book Description Statistical, machine learning and neural network approaches to classification are all covered in this volume. Contributions have been integrated to provide an objective assessment of the potential for machine learning algorithms in solving significant commercial and industrial problems, ...
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 fin... ebookslibrary 被引量: 0发表: 0年 Book review of: G...
Related Book Categories: Machine Learning Statistics and SAS Programming Data Analysis and Data Mining Probability, Stochastic Process, Queueing Theory, etc.Read and Download Links:The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition The Mirror Site (1) - PDF...
An Introduction to Statistical Learning (ISL) arose from the perceived need for a broader and less technical treatment of these topics. In this new book, we cover many of the same topics as ESL, but we concentrate more on the applications of the methods and less on the mathematical details...
machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book descibes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than ma...
This book 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 to marketing to astrophysics in the past t