Ensemble Machine Learning (Record no. 100571)

000 -LEADER
fixed length control field 02896nam a22004575i 4500
001 - CONTROL NUMBER
control field 978-1-4419-9326-7
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140220083234.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 120216s2012 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781441993267
-- 978-1-4419-9326-7
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-1-4419-9326-7
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q342
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM004000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Zhang, Cha.
Relator term editor.
245 10 - TITLE STATEMENT
Title Ensemble Machine Learning
Medium [electronic resource] :
Remainder of title Methods and Applications /
Statement of responsibility, etc edited by Cha Zhang, Yunqian Ma.
264 #1 -
-- Boston, MA :
-- Springer US,
-- 2012.
300 ## - PHYSICAL DESCRIPTION
Extent VIII, 329p. 84 illus.
Other physical details online resource.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
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-- rdamedia
338 ## -
-- online resource
-- cr
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347 ## -
-- text file
-- PDF
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505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction of Ensemble Learning -- Boosting Algorithms: Theory, Methods and Applications -- On Boosting Nonparametric Learners -- Super Learning -- Random Forest -- Ensemble Learning by Negative Correlation Learning -- Ensemble Nystrom Method -- Object Detection -- Ensemble Learning for Activity Recognition -- Ensemble Learning in Medical Applications -- Random Forest for Bioinformatics.
520 ## - SUMMARY, ETC.
Summary, etc It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face detection and are now being applied in areas as diverse as object trackingand bioinformatics.   Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including various contributions from researchers in leading industrial research labs. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Mining and Knowledge Discovery.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Science, general.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Ma, Yunqian.
Relator term editor.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781441993250
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4419-9326-7
912 ## -
-- ZDB-2-ENG

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