Téléchargez le livre : Rank-Based Methods for Shrinkage and Selection

Rank-Based Methods for Shrinkage and Selection

With Application to Machine Learning

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Éditeur :

Wiley


Paru le : 2022-04-12



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Description
Rank-Based Methods for Shrinkage and Selection
A practical and hands-on guide to the theory and methodology of statistical estimation based on rank
Robust statistics is an important field in contemporary mathematics and applied statistical methods. Rank-Based Methods for Shrinkage and Selection: With Application to Machine Learning describes techniques to produce higher quality data analysis in shrinkage and subset selection to obtain parsimonious models with outlier-free prediction. This book is intended for statisticians, economists, biostatisticians, data scientists and graduate students.
Rank-Based Methods for Shrinkage and Selection elaborates on rank-based theory and application in machine learning to robustify the least squares methodology. It also includes: Development of rank theory and application of shrinkage and selection Methodology for robust data science using penalized rank estimators Theory and methods of penalized rank dispersion for ridge, LASSO and Enet Topics include Liu regression, high-dimension, and AR(p) Novel rank-based logistic regression and neural networks Problem sets include R code to demonstrate its use in machine learning
Pages
480 pages
Collection
n.c
Parution
2022-04-12
Marque
Wiley
EAN papier
9781119625391
EAN PDF
9781119625414
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
480
Taille du fichier
26849 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
128,66 €
EAN EPUB
9781119625421
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
480
Taille du fichier
29983 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
128,66 €

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