The Elements of Statistical Learning Data Mining, Inference and Prediction

Name: The Elements of Statistical Learning
Author: Trevor Hastie

Auteur: Trevor Hastie

Taal: Engels

Afbeeldingen

Artikel vergelijken

Vergelijk met andere artikelen

Bekijk nu

Auteur: Trevor Hastie Robert Tibshirani

Co-auteur: Jerome Friedman

Engels
Hardcover
9780387952840
31 december 2001
552 pagina's

Alle productspecificaties

Trevor Hastie

"Trevor John Hastie (born 27 June 1953) is a South African and American statistician and computer scientist. He is currently serving as the John A. Overdeck Professor of Mathematical Sciences and Professor of Statistics at the Stanford University. Hastie is known for his contributions to applied statistics, especially in the field of machine learning, data mining, and bioinformatics. He has authored several popular books in statistical learning, including The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Hastie has been listed as an ISI Highly Cited Author in Mathematics by the ISI Web of Knowledge.

(Bron: Wikipedia. Beschikbaar onder de licentie Creative Commons Naamsvermelding/Gelijk delen.)"

Alles van Trevor Hastie

Samenvatting

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 should be 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. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap . Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

Productspecificaties

Inhoud

Taal: en
Bindwijze: Hardcover
Oorspronkelijke releasedatum: 31 december 2001
Aantal pagina's: 552
Illustraties: Nee

Betrokkenen

Hoofdauteur: Trevor Hastie
Tweede Auteur: Robert Tibshirani
Co Auteur: Jerome Friedman
Hoofduitgeverij: Springer-Verlag Telos

Overige kenmerken

Editie: 2001. Corr. 3rd
Product breedte: 163 mm
Product hoogte: 42 mm
Product lengte: 241 mm
Studieboek: Ja
Verpakking breedte: 155 mm
Verpakking hoogte: 235 mm
Verpakking lengte: 235 mm
Verpakkingsgewicht: 1100 g

EAN

EAN: 9780387952840

Je vindt dit artikel in

Categorieën: Wetenschap & Natuur

Computers & Informatica

Computertechnologie

Databases

Biologie

Wiskunde

Kunstmatige intelligentie

Data mining

Kansrekening & Statistieken

Toegepaste wiskunde

Cognitieve systemen

Stochastisch proces

Boeken
Taal: Engels
Beschikbaarheid: Leverbaar
Boek, ebook of luisterboek?: Boek
Studieboek of algemeen: Studieboeken

Reviews

Nog geen reviews

Hoe controleren en plaatsen wij reviews? Hoe controleren en plaatsen wij reviews?

Negatief, positief, neutraal: we zetten een review altijd online. We controleren wel eerst of ’ie voldoet aan onze reviewvoorwaarden en niet nep is. We controleren ook of ’ie is geschreven door iemand die het artikel heeft gekocht via bol.com en zetten dit er dan bij. De controles gebeuren automatisch, al kijken er soms mensen mee. Bol.com betaalt niet voor reviews. Als een reviewer door een andere partij is vergoed, staat dit in de review zelf.