The elements of statistical learning (Record no. 51411)

MARC details
000 -LEADER
fixed length control field 03080cam a22003255a 4500
003 - CONTROL NUMBER IDENTIFIER
control field ISURa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 081106s2009 nyua b 001 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780387848570
International Standard Book Number 9780387848587
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title English Language
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3122
Edition number HAS
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Hastie, Trevor
9 (RLIN) 72279
245 14 - TITLE STATEMENT
Title The elements of statistical learning
Remainder of title data mining, inference, and prediction
250 ## - EDITION STATEMENT
Edition statement 2nd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc New York, NY :
Name of publisher, distributor, etc Springer,
Date of publication, distribution, etc 2009.
300 ## - PHYSICAL DESCRIPTION
Extent xxii, 745 p. :
Dimensions 25 cm.
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Springer series in statistics.
9 (RLIN) 72280
500 ## - GENERAL NOTE
General note 1. Introduction --<br/>2. Overview of supervised learning --<br/>3. Linear methods for regression --<br/>4. Linear methods for classification --<br/>5. Basis expansions and regularization --<br/>6. Kernel smoothing methods --<br/>7. Model assessment and selection --<br/>8. Model inference and averaging --<br/>9. Additive models, trees, and related methods --<br/>10. Boosting and additive trees --<br/>11. Neural networks --<br/>12. Support vector machines and flexible discriminants --<br/>13. Prototype methods and nearest-neighbors --<br/>14. Unsupervised learning --<br/>15. Random forests --<br/>16. Ensemble learning --<br/>17. Undirected graphical models
520 ## - SUMMARY, ETC.
Summary, etc "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 and 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."--Publisher's description.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning.
9 (RLIN) 69133
Topical term or geographic name as entry element Statistics
General subdivision Methodology.
9 (RLIN) 72281
Topical term or geographic name as entry element Data mining.
9 (RLIN) 29634
Topical term or geographic name as entry element Bioinformatics.
9 (RLIN) 4946
Topical term or geographic name as entry element Inference.
9 (RLIN) 72282
Topical term or geographic name as entry element Forecasting.
9 (RLIN) 376
Topical term or geographic name as entry element Computational intelligence.
9 (RLIN) 1589
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Tibshirani, Robert
9 (RLIN) 72283
Personal name Friedman, J. H.
9 (RLIN) 72284
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Lending Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Date checked out Price effective from Koha item type
    Dewey Decimal Classification     Lending Collection Applied Sciences Library Applied Sciences Library Lending Section 23/05/2019 12530.50 1 519.5 HAS 112944 10/03/2022 23/02/2022 27/05/2019 Lending Books
    Dewey Decimal Classification     Reference Collection Applied Sciences Library Applied Sciences Library Reference Section 23/05/2019 12530.50 1 519.5 HAS 112945 30/12/2020 13/02/2020 27/05/2019 Sheduled Reference