Ensemble classification methods : With applications in R (Record no. 760609)

MARC details
000 -LEADER
fixed length control field 02331nam a2200229 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119421092
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title English
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5
Item number ENS
084 ## - OTHER CLASSIFICATION NUMBER
Source of Number Colon Classification
Classification number 325.5/ENS
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Nil.
245 ## - TITLE STATEMENT
Title Ensemble classification methods : With applications in R
Statement of responsibility, etc / Edited by Alfaro Esteban,Gamez Matias and Garcia Noelia
250 ## - EDITION STATEMENT
Edition statement 1
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication UK:
Name of publisher Wiley,
Year of publication 2019.
300 ## - PHYSICAL DESCRIPTION
Number of Pages 200p.
500 ## - GENERAL NOTE
General note Ensemble Classification Methods with Applications in R introduces the concepts and principles of ensemble classifier methods and includes a review of the most commonly used techniques. This important resource shows how ensemble classification has become an extension of the individual classifiers. The text places emphasis on two areas of machine learning: classification trees and ensemble learning. The authors explore ensemble classification methods' basic characteristics and explain the types of problems that can emerge in its application.Written by a team of noted experts in the field, the text is divided into two main sections. The first section outlines the theoretical underpinnings of the topic and the second section is designed to include examples of practical applications. The book contains a wealth of illustrative cases of business failure prediction, zoology, ecology and others. This vital guide:Offers an important text that has been tested both in the classroom and at tutorials at conferencesContains authoritative information written by leading experts in the field Presents a comprehensive text that can be applied to courses in machine learning, data mining and artificial intelligenceCombines in one volume, two of the most intriguing topics in machine learning: ensemble learning and classification treesWritten for researchers from many fields such as biostatistics, economics, environment, zoology, as well as students of data mining and machine learning, Ensemble Classification Methods with Applications in R puts the focus on two topics in machine learning: classification trees and ensemble learning.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Statistical mathematics/ and R Applications in Statistics
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Alfaro Esteban (ed.)
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Gamez Matias (ed.)
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Garcia Noelia (ed.)
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Book
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home Library Current Location Shelving location Date acquired Source of acquisition Cost, normal purchase price Full call number Accession Number Price effective from Koha item type
    Dewey Decimal Classification   Not For Loan Reference Dept. of Economics Dept. of Economics Processing Center 03/03/2026 ABD-33 Dtd 25/02/2026 6364.00 519.5 ENS ECN17032 03/03/2026 Book