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An Introduction to Statistical Learning [[electronic resource] ] : with Applications in Python / / by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, Jonathan Taylor
An Introduction to Statistical Learning [[electronic resource] ] : with Applications in Python / / by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, Jonathan Taylor
Autore James Gareth
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (617 pages)
Disciplina 519.5
Altri autori (Persone) WittenDaniela
HastieTrevor
TibshiraniRobert
TaylorJonathan
Collana Springer Texts in Statistics
Soggetto topico Statistics
Mathematical statistics - Data processing
Statistical Theory and Methods
Statistics and Computing
Applied Statistics
Estadística matemàtica
Models matemàtics
Python (Llenguatge de programació)
Soggetto genere / forma Llibres electrònics
ISBN 9783031387470
3-031-38747-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction -- Statistical Learning -- Linear Regression -- Classification -- Resampling Methods -- Linear Model Selection and Regularization -- Moving Beyond Linearity -- Tree-Based Methods -- Support Vector Machines -- Deep Learning -- Survival Analysis and Censored data -- Unsupervised Learning -- Multiple Testing -- Index.
Record Nr. UNINA-9910734891903321
James Gareth  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
An Introduction to Statistical Learning : with Applications in R / / by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
An Introduction to Statistical Learning : with Applications in R / / by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
Autore James Gareth (Gareth Michael)
Edizione [Second Edition.]
Pubbl/distr/stampa New York, NY : , : Springer US : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (xv, 607 p : il. col.)
Collana Springer Texts in Statistics
Soggetto topico Statistics
Mathematical statistics - Data processing
Artificial intelligence
Statistical Theory and Methods
Statistics and Computing
Artificial Intelligence
Estadística matemàtica
Models matemàtics
R (Llenguatge de programació)
Soggetto genere / forma Llibres electrònics
ISBN 1-0716-1418-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface -- 1 Introduction -- 2 Statistical Learning -- 3 Linear Regression -- 4 Classification -- 5 Resampling Methods -- 6 Linear Model Selection and Regularization -- 7 Moving Beyond Linearity -- 8 Tree-Based Methods -- 9 Support Vector Machines -- 10 Deep Learning -- 11 Survival Analysis and Censored Data -- 12 Unsupervised Learning -- 13 Multiple Testing -- Index.
Record Nr. UNISA-996466401603316
James Gareth (Gareth Michael)  
New York, NY : , : Springer US : , : Imprint : Springer, , 2021
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
An Introduction to Statistical Learning : with Applications in R / / by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
An Introduction to Statistical Learning : with Applications in R / / by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
Autore James Gareth (Gareth Michael)
Edizione [Second Edition.]
Pubbl/distr/stampa New York, NY : , : Springer US : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (xv, 607 p : il. col.)
Collana Springer Texts in Statistics
Soggetto topico Statistics
Mathematical statistics - Data processing
Artificial intelligence
Statistical Theory and Methods
Statistics and Computing
Artificial Intelligence
Estadística matemàtica
Models matemàtics
R (Llenguatge de programació)
Soggetto genere / forma Llibres electrònics
ISBN 1-0716-1418-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface -- 1 Introduction -- 2 Statistical Learning -- 3 Linear Regression -- 4 Classification -- 5 Resampling Methods -- 6 Linear Model Selection and Regularization -- 7 Moving Beyond Linearity -- 8 Tree-Based Methods -- 9 Support Vector Machines -- 10 Deep Learning -- 11 Survival Analysis and Censored Data -- 12 Unsupervised Learning -- 13 Multiple Testing -- Index.
Record Nr. UNINA-9910495188803321
James Gareth (Gareth Michael)  
New York, NY : , : Springer US : , : Imprint : Springer, , 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
An Introduction to Statistical Learning [[electronic resource] ] : with Applications in R / / by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
An Introduction to Statistical Learning [[electronic resource] ] : with Applications in R / / by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
Autore James Gareth
Edizione [1st ed. 2013.]
Pubbl/distr/stampa New York, NY : , : Springer New York : , : Imprint : Springer, , 2013
Descrizione fisica 1 online resource (XIV, 426 p. 150 illus., 146 illus. in color.)
Disciplina 519.5
Collana Springer Texts in Statistics
Soggetto topico Statistics 
Artificial intelligence
R (Computer program language)
Statistical Theory and Methods
Statistics and Computing/Statistics Programs
Artificial Intelligence
Statistics, general
ISBN 1-4614-7138-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction -- Statistical Learning -- Linear Regression -- Classification -- Resampling Methods -- Linear Model Selection and Regularization -- Moving Beyond Linearity -- Tree-Based Methods -- Support Vector Machines -- Unsupervised Learning -- Index.
Record Nr. UNINA-9910438159503321
James Gareth  
New York, NY : , : Springer New York : , : Imprint : Springer, , 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui