Hastie, Trevor
Overview
Works:  69 works in 211 publications in 2 languages and 2,069 library holdings 

Roles:  Author, Thesis advisor, Editor 
Classifications:  Q325.75, 006.31 
Publication Timeline
.
Most widely held works by
Trevor Hastie
The elements of statistical learning : data mining, inference, and prediction : with 200 fullcolor illustrations by
Trevor Hastie(
Book
)
24 editions published between 2001 and 2013 in English and held by 632 WorldCat member libraries worldwide
Describes important statistical ideas in machine learning, data mining, and bioinformatics. Covers a broad range, from supervised learning (prediction), to unsupervised learning, including classification trees, neural networks, and support vector machines
24 editions published between 2001 and 2013 in English and held by 632 WorldCat member libraries worldwide
Describes important statistical ideas in machine learning, data mining, and bioinformatics. Covers a broad range, from supervised learning (prediction), to unsupervised learning, including classification trees, neural networks, and support vector machines
Generalized additive models by
Trevor Hastie(
Book
)
42 editions published between 1984 and 1999 in English and Undetermined and held by 586 WorldCat member libraries worldwide
Likelihood based regression models, such as the normal linear regression model and the linear logistic model, assume a linear (or some other parametric) form for the covariate effects. The authors introduce the Local Scoring procedure which is applicable to any likelihoodbased regression model: the class of Generalized Linear Models contains many of these. In this class the Local Scoring procedure replaces a linear predictor by a additive predictor; hence the name Generalized Additive Models. Local Scoring can also be applied to nonstandard models like Cox's proportional hazards model for survival data
42 editions published between 1984 and 1999 in English and Undetermined and held by 586 WorldCat member libraries worldwide
Likelihood based regression models, such as the normal linear regression model and the linear logistic model, assume a linear (or some other parametric) form for the covariate effects. The authors introduce the Local Scoring procedure which is applicable to any likelihoodbased regression model: the class of Generalized Linear Models contains many of these. In this class the Local Scoring procedure replaces a linear predictor by a additive predictor; hence the name Generalized Additive Models. Local Scoring can also be applied to nonstandard models like Cox's proportional hazards model for survival data
An introduction to statistical learning : with applications in R by
Gareth James(
Book
)
12 editions published between 2013 and 2015 in English and held by 257 WorldCat member libraries worldwide
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, treebased methods, support vector machines, clustering, and more. Color graphics and realworld examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors cowrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and nonstatisticians alike who wish to use cuttingedge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra
12 editions published between 2013 and 2015 in English and held by 257 WorldCat member libraries worldwide
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, treebased methods, support vector machines, clustering, and more. Color graphics and realworld examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors cowrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and nonstatisticians alike who wish to use cuttingedge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra
Statistical models in S(
Book
)
31 editions published between 1991 and 1999 in English and Japanese and held by 255 WorldCat member libraries worldwide
31 editions published between 1991 and 1999 in English and Japanese and held by 255 WorldCat member libraries worldwide
Statistical learning with sparsity : the lasso and generalizations by
Trevor Hastie(
Book
)
14 editions published in 2015 in English and Undetermined and held by 80 WorldCat member libraries worldwide
Discover New Methods for Dealing with HighDimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data.Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm for its computation. They discuss the application of ℓ1 penalties to generalized l
14 editions published in 2015 in English and Undetermined and held by 80 WorldCat member libraries worldwide
Discover New Methods for Dealing with HighDimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data.Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm for its computation. They discuss the application of ℓ1 penalties to generalized l
Estimation of additive principal components using penalized least squares : implementation in S by
Andreas Buja(
Book
)
1 edition published in 1992 in English and held by 5 WorldCat member libraries worldwide
1 edition published in 1992 in English and held by 5 WorldCat member libraries worldwide
Additive logistic regression : a statistical view of boosting by
J. H Friedman(
Book
)
3 editions published in 1998 in English and held by 3 WorldCat member libraries worldwide
3 editions published in 1998 in English and held by 3 WorldCat member libraries worldwide
Tōkeiteki gakushū no kiso : dēta mainingu suiron yosoku(
Book
)
2 editions published in 2014 in Japanese and held by 3 WorldCat member libraries worldwide
2 editions published in 2014 in Japanese and held by 3 WorldCat member libraries worldwide
Bayesian backfitting by
Trevor Hastie(
Book
)
4 editions published in 1998 in English and held by 3 WorldCat member libraries worldwide
4 editions published in 1998 in English and held by 3 WorldCat member libraries worldwide
Principal curves and surfaces by
Trevor Hastie(
Book
)
3 editions published in 1984 in English and held by 2 WorldCat member libraries worldwide
3 editions published in 1984 in English and held by 2 WorldCat member libraries worldwide
Estimating the number of clusters in a dataset via the gap statistic by
Robert Tibshirani(
Book
)
3 editions published in 2000 in English and held by 2 WorldCat member libraries worldwide
3 editions published in 2000 in English and held by 2 WorldCat member libraries worldwide
Principal component models for sparse functional data by Gareth James(
Book
)
3 editions published in 1999 in English and held by 2 WorldCat member libraries worldwide
3 editions published in 1999 in English and held by 2 WorldCat member libraries worldwide
Statistical models for image sequences by
Neil Crellin(
Book
)
3 editions published in 1999 in English and held by 2 WorldCat member libraries worldwide
3 editions published in 1999 in English and held by 2 WorldCat member libraries worldwide
Discriminant adaptive nearest neighbor classification by
Trevor Hastie(
Book
)
4 editions published in 1994 in English and held by 2 WorldCat member libraries worldwide
4 editions published in 1994 in English and held by 2 WorldCat member libraries worldwide
Degrees of freedom tests for smoothing splines by
Eva Cantoni(
Book
)
3 editions published in 2000 in English and held by 2 WorldCat member libraries worldwide
3 editions published in 2000 in English and held by 2 WorldCat member libraries worldwide
Sparse discriminant analysis by
Line Clemmensen(
Book
)
1 edition published in 2008 in English and held by 2 WorldCat member libraries worldwide
1 edition published in 2008 in English and held by 2 WorldCat member libraries worldwide
Classification by pairwise coupling by
Trevor Hastie(
Book
)
2 editions published between 1996 and 1997 in English and held by 1 WorldCat member library worldwide
2 editions published between 1996 and 1997 in English and held by 1 WorldCat member library worldwide
Dynamic mixtures of splines : a model for saliency grouping in the time frequency plane by
Stanford University(
Book
)
2 editions published in 1997 in English and held by 1 WorldCat member library worldwide
2 editions published in 1997 in English and held by 1 WorldCat member library worldwide
Conditional random sampling : a sketchbased sampling technique for sparse data by Ping Li(
Book
)
2 editions published in 2006 in English and held by 1 WorldCat member library worldwide
2 editions published in 2006 in English and held by 1 WorldCat member library worldwide
Practical procedures for dimension reduction in l₁ by Ping Li(
Book
)
2 editions published in 2006 in English and held by 1 WorldCat member library worldwide
2 editions published in 2006 in English and held by 1 WorldCat member library worldwide
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Related Identities
 Tibshirani, Robert Thesis advisor Author Contributor
 Friedman, J. H. (Jerome H.) Author
 Witten, Daniela
 Chambers, John M. 1941 Author Editor
 James, Gareth (Gareth Michael) Author
 Wainwright, Martin Author Contributor
 Friedman, Jerome
 James, Gareth Author
 Friedman, Jerome (Jerome H.)
 United States Public Health Service
Useful Links
Associated Subjects
Artificial intelligence Bayesian statistical decision theory Bioinformatics BiologyData processing Computational biology Computational intelligence Computer science Database management Data mining Electronic data processing Estimation theory Forecasting Inference Least squares Linear models (Statistics) Linear models (Statistics)Computer programs Machine learning Mathematical models Mathematical statistics Mathematical statisticsData processing MathematicsData processing Multivariate analysis Paired comparisons (Statistics) Principal components analysis Proof theory R (Computer program language) Random walks (Mathematics) Regression analysis S (Computer program language) Smoothing (Statistics) Sparse matrices Spline theory Statistics StatisticsGraphic methods StatisticsMethodology Supervised learning (Machine learning)
Alternative Names
Hastie, T. J.
Hastie, T. J. 1953
Hastie, T. J. (Trevor J.)
Hastie, T. J. (Trevor J.), 1953
Hastie, Trevor.
Hastie, Trevor 1953...
Hastie, Trevor J.
Hastie, Trevor J. 1953
Trevor Hastie Amerikaans statisticus
Trevor Hastie statisticien
Trevor Hastie statistico statunitense
Trevor Hastie statistiker
Trevor J. Hastie
Тревор Хасти
ヘイスティ, T. J
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