
Classification and Regression Trees
CRC Press
1st Edition
Published on 29. August 2017
Book
Hardback
368 pages
978-1-138-46952-5 (ISBN)
Description
The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Professional and Professional Practice & Development
Dimensions
Height: 234 mm
Width: 156 mm
Weight
840 gr
ISBN-13
978-1-138-46952-5 (9781138469525)
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

Leo Breiman | Jerome Friedman | Charles J. Stone
Classification and Regression Trees
E-Book
10/2017
1st Edition
Chapman & Hall/CRC
€165.99
Available for download

Leo Breiman | Jerome Friedman | Charles J. Stone
Classification and Regression Trees
E-Book
10/2017
1st Edition
Chapman & Hall/CRC
€165.99
Available for download

Leo Breiman | Jerome Friedman | Charles J. Stone
Classification and Regression Trees
Book
01/1984
1st Edition
Chapman & Hall/CRC
€172.50
Shipment within 10-20 days
Persons
Breiman, Leo
Author
Consultant, Berkeley, California, USA
Stanford University, California, USA
University of California, Berkeley, USA
Stanford, California, USA
Content
Preface, Chapter 1 BACKGROUND, Chapter 2 INTRODUCTION TO TREE CLASSIFICATION, Chapter 3 RIGHT SIZED TREES AND HONEST ESTIMATES, Chapter 4 SPLITTING RULES, Chapter 5 STRENGTHENING AND INTERPRETING, Chapter 6 MEDICAL DIAGNOSIS AND PROGNOSIS, Chapter 7 MASS SPECTRA CLASSIFICATION, Chapter 8 REGRESSION TREE, Chapter 9 BAYES RULES AND PARTITIONS, Chapter 10 OPTIMAL PRUNING, Chapter 11 CONSTRUCTION OF TREES FROM A LEARNING SAMPLE, Chapter 12 CONSISTENCY, Bibliography, Notation Index, Subject Index