
Rank-Based Methods for Shrinkage and Selection
With Application to Machine Learning
Wiley-Blackwell (Publisher)
1st Edition
Published on 12. April 2022
Book
Hardback
480 pages
978-1-119-62539-1 (ISBN)
Description
The book aims to accumulate the different theory and methods for selection and shrinkage estimation based on rank order. These theories are intended to be systematically organized to serve as a guide for researchers in this field. Ridge regression and LASSO are at the center of all penalty estimators in a range of standard models that are used in many applied statistical analysis and machine learning. Written by noted experts in this field, this book contains a through introduction to robust rank-based penalty and shrinkage estimations and explores role of ridge, LASSO and Elastic Net play in the computer intuitive environment for big data analysis. Designed to be accessible, this book presets detailed coverage of the basic terminology related to the various models such as the location and simple linear models, and rank-theory based ridge, LASSO and Elastic Net and Sein-type estimators. This book provides a unified presentation of various methods in one book and has potential use in machine learning.
More details
Language
English
Place of publication
Hoboken
United States
Publishing group
John Wiley and Sons Ltd
Target group
Professional and scholarly
Dimensions
Height: 235 mm
Width: 157 mm
Thickness: 30 mm
Weight
845 gr
ISBN-13
978-1-119-62539-1 (9781119625391)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

A. K. Md. Ehsanes Saleh | Mohammad Arashi | Resve A. Saleh
Rank-Based Methods for Shrinkage and Selection
With Application to Machine Learning
E-Book
04/2022
1st Edition
Wiley
€113.99
Available for download

A. K. Md. Ehsanes Saleh | Mohammad Arashi | Resve A. Saleh
Rank-Based Methods for Shrinkage and Selection
With Application to Machine Learning
E-Book
03/2022
1st Edition
Wiley
€109.99
Available for download
Persons
A. K. Md. EHSANES SALEH, PhD, is a professor emeritus and distinguished research professor in the school of Mathematics and Statistics, Carleton University, Canada. Dr. Saleh is author of Theory of Preliminary Test and Stein-Type Estimation with Applications, and co-author of An Introduction to Probability and Statistics, 2nd Edition, Statistical Inference for Models with Multivariate t-Distributed Errors, and Theory of Ridge Regression Estimation with Applications, all published by Wiley.
M. Arashi, PhD, is an Associate Professor at Shahrood University of Technology, Iran and Extraordinary Professor and C2 rated researcher at University of Pretoria, South Africa. Dr. Arashi is co-author of Statistical Inference for Models with Multivariate t-Distributed Errors and Theory of Ridge Regression Estimation with Applications, both published by Wiley.
Mina Norouzirad, PhD, is Lecturer at Faculty of Mathematical Sciences, Shahrood University of Technology, Iran.
Author
Carleton University, Ottawa, Canada