資料來源:
三民書局
The elements of statistical learning : data mining, inference, and prediction / Trevor Hastie, Robert Tibshirani, Jerome Friedman
- 作者： Hastie, Trevor
- 其他作者：
- 其他題名：
- Springer series in statistics
- 出版： New York : Springer c2009
- 叢書名： Springer series in statistics
- 主題： Supervised learning (Machine learning)
- 版本：2nd ed.
- ISBN： 9780387848570 (hbk.) :: NT$1710.00 、 0387848576 (hbk.) 、 9780387848587 (ebk) 、 0387848584 (ebk)
- 書目註：Includes bibliographical references and indexes
-
讀者標籤：
- 系統號： 005129861 | 機讀編目格式
館藏資訊
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 mark
摘要註
"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."--Jacket