Applications of Supervised and Unsupervised Ensemble MethodsApplications of Supervised and Unsupervised Ensemble Methods

Applications of Supervised and Unsupervised Ensemble Methods
Author : Oleg Okun
Publisher : Springer Science & Business Media
Total Pages : 268
Release : 2009-10-06
ISBN 10 : 9783642039980
ISBN 13 : 3642039987
Language : EN, FR, DE, ES & NL

Applications of Supervised and Unsupervised Ensemble Methods Book Description:

Expanding upon presentations at last year’s SUEMA (Supervised and Unsupervised Ensemble Methods and Applications) meeting, this volume explores recent developments in the field. Useful examples act as a guide for practitioners in computational intelligence.

Applications of Supervised and Unsupervised Ensemble Methods
Language: en
Pages: 268
Authors: Oleg Okun
Categories: Computers
Type: BOOK - Published: 2009-10-06 - Publisher: Springer Science & Business Media

Expanding upon presentations at last year’s SUEMA (Supervised and Unsupervised Ensemble Methods and Applications) meeting, this volume explores recent develop
Ensemble Methods
Language: en
Pages: 236
Authors: Zhi-Hua Zhou
Categories: Business & Economics
Type: BOOK - Published: 2012-06-06 - Publisher: CRC Press

An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurat
Pattern Classification Using Ensemble Methods
Language: en
Pages: 244
Authors: Lior Rokach
Categories: Computers
Type: BOOK - Published: 2010 - Publisher: World Scientific

Researchers from various disciplines such as pattern recognition, statistics, and machine learning have explored the use of ensemble methodology since the late
Ensemble Learning: Pattern Classification Using Ensemble Methods (Second Edition)
Language: en
Pages: 300
Authors: Lior Rokach
Categories: Computers
Type: BOOK - Published: 2019-02-27 - Publisher: World Scientific

This updated compendium provides a methodical introduction with a coherent and unified repository of ensemble methods, theories, trends, challenges, and applica
Supervised and Unsupervised Ensemble Methods and their Applications
Language: en
Pages: 182
Authors: Oleg Okun
Categories: Computers
Type: BOOK - Published: 2008-04-18 - Publisher: Springer Science & Business Media

This book results from the workshop on Supervised and Unsupervised Ensemble Methods and their Applications (briefly, SUEMA) in June 2007 in Girona, Spain. This
Ensemble Learning Algorithms With Python
Language: en
Pages: 450
Authors: Jason Brownlee
Categories: Computers
Type: BOOK - Published: 2021-04-26 - Publisher: Machine Learning Mastery

Predictive performance is the most important concern on many classification and regression problems. Ensemble learning algorithms combine the predictions from m
Hands-On Ensemble Learning with R
Language: en
Pages: 376
Authors: Prabhanjan Narayanachar Tattar
Categories: Computers
Type: BOOK - Published: 2018-07-27 - Publisher: Packt Publishing Ltd

Explore powerful R packages to create predictive models using ensemble methods Key Features Implement machine learning algorithms to build ensemble-efficient mo
Data Mining and Knowledge Discovery Handbook
Language: en
Pages: 1383
Authors: Oded Maimon
Categories: Computers
Type: BOOK - Published: 2005 - Publisher: Springer Science & Business Media

Organizes major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD). This book
Particle Characterization: Light Scattering Methods
Language: en
Pages: 399
Authors: Renliang Xu
Categories: Science
Type: BOOK - Published: 2006-04-11 - Publisher: Springer Science & Business Media

Particle characterization is an important component in product research and development, manufacture, and quality control of particulate materials and an import
Fault Prediction Modeling for the Prediction of Number of Software Faults
Language: en
Pages: 78
Authors: Santosh Singh Rathore
Categories: Computers
Type: BOOK - Published: 2019-04-03 - Publisher: Springer

This book addresses software faults—a critical issue that not only reduces the quality of software, but also increases their development costs. Various models