Ensemble Learning

Pattern Classification Using Ensemble Methods

Nonfiction, Computers, Advanced Computing, Engineering, Computer Vision, Theory, General Computing
Cover of the book Ensemble Learning by Lior Rokach, World Scientific Publishing Company
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Lior Rokach ISBN: 9789811201974
Publisher: World Scientific Publishing Company Publication: February 27, 2019
Imprint: WSPC Language: English
Author: Lior Rokach
ISBN: 9789811201974
Publisher: World Scientific Publishing Company
Publication: February 27, 2019
Imprint: WSPC
Language: English

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.

Contents:

  • Introduction to Machine Learning
  • Classification and Regression Trees
  • Introduction to Ensemble Learning
  • Ensemble Classification
  • Gradient Boosting Machines
  • Ensemble Diversity
  • Ensemble Selection
  • Error Correcting Output Codes
  • Evaluating Ensembles of Classifiers

Readership: Professionals, researchers, academics, and graduate students in artificial intelligence, databases and machine learning.
0

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

Contents:

Readership: Professionals, researchers, academics, and graduate students in artificial intelligence, databases and machine learning.
0

More books from World Scientific Publishing Company

Cover of the book Mathematical Methods for the Natural and Engineering Sciences by Lior Rokach
Cover of the book Mathematics Problem-Solving Challenges for Secondary School Students and Beyond by Lior Rokach
Cover of the book Complexity-Intelligence Strategy by Lior Rokach
Cover of the book Economic Transition in China by Lior Rokach
Cover of the book Semiconductor Optical Amplifiers by Lior Rokach
Cover of the book Ethics in Tissue Establishments by Lior Rokach
Cover of the book An Introduction to the Analysis of Algorithms by Lior Rokach
Cover of the book Introduction to Modern Physics by Lior Rokach
Cover of the book Understanding and Preventing Sudden Death by Lior Rokach
Cover of the book Dynamics of Coastal Systems by Lior Rokach
Cover of the book International and Interregional Migration by Lior Rokach
Cover of the book Generalizations of Finite Metrics and Cuts by Lior Rokach
Cover of the book Particle Methods for Multi-Scale and Multi-Physics by Lior Rokach
Cover of the book An Operator Theory Problem Book by Lior Rokach
Cover of the book MOSFET Modeling for VLSI Simulation by Lior Rokach
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy