Ensemble Learning: Pattern Classification Using Ensemble Methods (Second Edition) PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Ensemble Learning: Pattern Classification Using Ensemble Methods (Second Edition) PDF full book. Access full book title Ensemble Learning: Pattern Classification Using Ensemble Methods (Second Edition) by Lior Rokach. Download full books in PDF and EPUB format.

Ensemble Learning: Pattern Classification Using Ensemble Methods (Second Edition)

Ensemble Learning: Pattern Classification Using Ensemble Methods (Second Edition) PDF Author: Lior Rokach
Publisher: World Scientific
ISBN: 9811201978
Category : Computers
Languages : en
Pages : 300

Get Book

Book Description
This updated compendium provides a methodical introduction with a coherent and unified repository of ensemble methods, theories, trends, challenges, and applications. More than a third of this edition comprised of new materials, highlighting descriptions of the classic methods, and extensions and novel approaches that have recently been introduced.Along with algorithmic descriptions of each method, the settings in which each method is applicable and the consequences and tradeoffs incurred by using the method is succinctly featured. R code for implementation of the algorithm is also emphasized.The unique volume provides researchers, students and practitioners in industry with a comprehensive, concise and convenient resource on ensemble learning methods.

Ensemble Learning: Pattern Classification Using Ensemble Methods (Second Edition)

Ensemble Learning: Pattern Classification Using Ensemble Methods (Second Edition) PDF Author: Lior Rokach
Publisher: World Scientific
ISBN: 9811201978
Category : Computers
Languages : en
Pages : 300

View

Book Description
This updated compendium provides a methodical introduction with a coherent and unified repository of ensemble methods, theories, trends, challenges, and applications. More than a third of this edition comprised of new materials, highlighting descriptions of the classic methods, and extensions and novel approaches that have recently been introduced.Along with algorithmic descriptions of each method, the settings in which each method is applicable and the consequences and tradeoffs incurred by using the method is succinctly featured. R code for implementation of the algorithm is also emphasized.The unique volume provides researchers, students and practitioners in industry with a comprehensive, concise and convenient resource on ensemble learning methods.

Pattern Classification Using Ensemble Methods

Pattern Classification Using Ensemble Methods PDF Author: Lior Rokach
Publisher: World Scientific
ISBN: 9814271071
Category : Computers
Languages : en
Pages : 244

View

Book Description
Researchers from various disciplines such as pattern recognition, statistics, and machine learning have explored the use of ensemble methodology since the late seventies. Thus, they are faced with a wide variety of methods, given the growing interest in the field. This book aims to impose a degree of order upon this diversity by presenting a coherent and unified repository of ensemble methods, theories, trends, challenges and applications. The book describes in detail the classical methods, as well as the extensions and novel approaches developed recently. Along with algorithmic descriptions of each method, it also explains the circumstances in which this method is applicable and the consequences and the trade-offs incurred by using the method. Sample Chapter(s). Chapter 1: Introduction to Pattern Classification (246 KB). Contents: Introduction to Pattern Classification; Introduction to Ensemble Learning; Ensemble Classification; Ensemble Diversity; Ensemble Selection; Error Correcting Output Codes; Evaluating Ensembles of Classifiers. Readership: Researchers, advanced undergraduate and graduate students in machine learning and pattern recognition.

Ensemble Learning

Ensemble Learning PDF Author: Lior Rokach
Publisher:
ISBN: 9789811201967
Category : COMPUTERS
Languages : en
Pages : 301

View

Book Description


Combining Pattern Classifiers

Combining Pattern Classifiers PDF Author: Ludmila I. Kuncheva
Publisher: John Wiley & Sons
ISBN: 1118315235
Category : Technology & Engineering
Languages : en
Pages : 384

View

Book Description
A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition The art and science of combining pattern classifiers has flourished into a prolific discipline since the first edition of Combining Pattern Classifiers was published in 2004. Dr. Kuncheva has plucked from the rich landscape of recent classifier ensemble literature the topics, methods, and algorithms that will guide the reader toward a deeper understanding of the fundamentals, design, and applications of classifier ensemble methods. Thoroughly updated, with MATLAB® code and practice data sets throughout, Combining Pattern Classifiers includes: Coverage of Bayes decision theory and experimental comparison of classifiers Essential ensemble methods such as Bagging, Random forest, AdaBoost, Random subspace, Rotation forest, Random oracle, and Error Correcting Output Code, among others Chapters on classifier selection, diversity, and ensemble feature selection With firm grounding in the fundamentals of pattern recognition, and featuring more than 140 illustrations, Combining Pattern Classifiers, Second Edition is a valuable reference for postgraduate students, researchers, and practitioners in computing and engineering.

Evolutionary Optimization and Ensemble Techniques for Data Mining and Pattern Recognition

Evolutionary Optimization and Ensemble Techniques for Data Mining and Pattern Recognition PDF Author: Alexander P. Topchy
Publisher: Ann Arbor, Mich. : University Microfilms International
ISBN:
Category : Data mining
Languages : en
Pages : 344

View

Book Description


Ensemble Methods

Ensemble Methods PDF Author: Zhi-Hua Zhou
Publisher: CRC Press
ISBN: 1439830037
Category : Business & Economics
Languages : en
Pages : 236

View

Book Description
An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field. After presenting background and terminology, the book covers the main algorithms and theories, including Boosting, Bagging, Random Forest, averaging and voting schemes, the Stacking method, mixture of experts, and diversity measures. It also discusses multiclass extension, noise tolerance, error-ambiguity and bias-variance decompositions, and recent progress in information theoretic diversity. Moving on to more advanced topics, the author explains how to achieve better performance through ensemble pruning and how to generate better clustering results by combining multiple clusterings. In addition, he describes developments of ensemble methods in semi-supervised learning, active learning, cost-sensitive learning, class-imbalance learning, and comprehensibility enhancement.

Multiple Classifier Systems

Multiple Classifier Systems PDF Author: Friedhelm Schwenker
Publisher: Springer
ISBN: 3319202480
Category : Computers
Languages : en
Pages : 231

View

Book Description
This book constitutes the refereed proceedings of the 12th International Workshop on Multiple Classifier Systems, MCS 2015, held in G├╝nzburg, Germany, in June/July 2015. The 19 revised papers presented were carefully reviewed and selected from 25 submissions. The papers address issues in multiple classifier systems and ensemble methods, including pattern recognition, machine learning, neural network, data mining and statistics. They are organized in topical sections on theory and algorithms and application and evaluation.

A New Design of Multiple Classifier System and Its Application to Classification of Time Series Data

A New Design of Multiple Classifier System and Its Application to Classification of Time Series Data PDF Author: Lei Chen
Publisher:
ISBN:
Category :
Languages : en
Pages :

View

Book Description


Multi-class Pattern Classification Using Neural Networks

Multi-class Pattern Classification Using Neural Networks PDF Author: Guobin Ou
Publisher:
ISBN:
Category : Computer network architectures
Languages : en
Pages : 128

View

Book Description


Supervised and Unsupervised Ensemble Methods and their Applications

Supervised and Unsupervised Ensemble Methods and their Applications PDF Author: Oleg Okun
Publisher: Springer Science & Business Media
ISBN: 3540789804
Category : Computers
Languages : en
Pages : 182

View

Book Description
This book results from the workshop on Supervised and Unsupervised Ensemble Methods and their Applications (briefly, SUEMA) in June 2007 in Girona, Spain. This workshop was held alongside the 3rd Iberian Conference on Pattern Recognition and Image Analysis.