The elements of statistical learning: data mining, inference, and prediction
(Book)

Book Cover
Contributors:
Published:
New York : Springer, [2009].
Format:
Book
Edition:
2nd ed.
Physical Desc:
xxii, 745 pages : illustrations (some color) ; 24 cm.
Status:
Copies
Location
Call Number
Status
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ASU Main (3rd floor)
Q325.75 .H37 2009
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Citations
APA Citation (style guide)

Hastie, T., Tibshirani, R., & Friedman, J. H. (2009). The elements of statistical learning: data mining, inference, and prediction. 2nd ed. New York, Springer.

Chicago / Turabian - Author Date Citation (style guide)

Hastie, Trevor, Robert, Tibshirani and J. H. Friedman. 2009. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York, Springer.

Chicago / Turabian - Humanities Citation (style guide)

Hastie, Trevor, Robert, Tibshirani and J. H. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York, Springer, 2009.

MLA Citation (style guide)

Hastie, Trevor,, et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd ed. New York, Springer, 2009.

Note! Citation formats are based on standards as of July 2022. Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy.
Description

"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.

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Language:
English
ISBN:
9780387848570, 0387848576

Notes

Bibliography
Includes bibliographical references (pages [699]-727) and indexes.
Description
"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.
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Last File Modification TimeFeb 21, 2024 06:17:12 AM
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