02995cam a22003975a 4500 25535 25535 15512507 BR-ReIFE 20200626104343.0 081106s2009 nyua b 001 0 eng 2008941148 9780387848570 (hardcover : alk. paper) 9780387848587 (electronic) DLC DLC DLC Q325.5 .H39 2009 006.3/1 22 006.31 H356e 2 ed. Hastie, Trevor 2554 The elements of statistical learning : data mining, inference, and prediction / Trevor Hastie, Robert Tibshirani, Jerome Friedman. 2nd ed. New York, NY : Springer, c2009. xxii, 745 p. : il. ; col. ; 25 cm. Springer series in statistics, 0172-7397 Inclui bibliografia, referências e índices. (p. [699]-727). 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. Aprendizado do computador 2556 Estatística 2572 Mineração de dados (Computação) 2557 Bioinformática 2561 Inferência (Lógica) 2559 Inteligência computacional 2562 Tibshirani, Robert 2569 Friedman, J. H. (Jerome H.) 2568 Springer Series in Statistics (Springer) ddc LV 0 0 ddc 0 1 NFIC 013 013 AG 2017-11-07 Compra 322.68 223581 0 006.31 H356e 8564244114 2020-02-05 00:00:00 Ex. 1 2020-02-05 LV 0 0 ddc 0 0 NFIC 013 013 AG 2017-11-07 Compra 322.68 223582 0 006.31 H356e 8564244115 2020-02-05 00:00:00 Ex. 2 2020-02-05 LV 0 0 ddc 0 0 NFIC 013 013 AG 2017-11-07 Compra 322.68 223583 0 006.31 H356e 8564244116 2020-02-05 00:00:00 Ex. 3 2020-02-05 LV 0 0 ddc 0 0 NFIC 013 013 AG 2017-11-07 Compra 322.68 223584 0 006.31 H356e 8564244117 2020-02-05 00:00:00 Ex. 4 2020-02-05 LV