During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. 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 not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for "wide" data (p bigger than n), including multiple testing and false discovery rates.

Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.

统计学的思想和各种统计数据对政府、社会乃至我们的工作和日常生活都产生着直接的影响，这种影响可能远远超乎你的想像。通过阅读本书，你将对我们这个世界有一个更完整、更清晰的认识。 本书一点儿也不枯燥乏味，恰恰相反，它是那样生动有趣，深入浅出地把统计学的概念和分析方法呈现在你面前。通过一个个真实的小故事，本书能让你在会心的微笑中不知不觉地增长专业知识，提高分析水平。这是一本能给你带来乐趣的书，也是一本能让你更加睿智的书。

《20世纪统计怎样变革了科学:女士品茶》以某位喝茶的英国女士的假设学说为起点，引出了近代数理统计的开创者——费歇尔，以及费歇尔为解决类似问题而发明的实验设计法。书中细数了二十世纪参与这场科学变革的代表性人物与事迹。