Multiple Classifier Systems (Record no. 175048)

MARC details
000 -LEADER
fixed length control field 06698nam a22006135i 4500
001 - CONTROL NUMBER
control field 978-3-540-25966-4
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423125154.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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fixed length control field 121227s2004 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783540259664
-- 978-3-540-25966-4
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/b98227
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q334-342
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA347.A78
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM004000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 23
245 10 - TITLE STATEMENT
Title Multiple Classifier Systems
Medium [electronic resource] :
Remainder of title 5th International Workshop, MCS 2004, Cagliari, Italy, June 9-11, 2004, Proceedings /
Statement of responsibility, etc edited by Fabio Roli, Josef Kittler, Terry Windeatt.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2004.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2004.
300 ## - PHYSICAL DESCRIPTION
Extent XII, 392 p.
Other physical details online resource.
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-- online resource
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490 1# - SERIES STATEMENT
Series statement Lecture Notes in Computer Science,
International Standard Serial Number 1611-3349 ;
Volume number/sequential designation 3077
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Invited Papers -- Classifier Ensembles for Changing Environments -- A Generic Sensor Fusion Problem: Classification and Function Estimation -- Bagging and Boosting -- AveBoost2: Boosting for Noisy Data -- Bagging Decision Multi-trees -- Learn++.MT: A New Approach to Incremental Learning -- Beyond Boosting: Recursive ECOC Learning Machines -- Exact Bagging with k-Nearest Neighbour Classifiers -- Combination Methods -- Yet Another Method for Combining Classifiers Outputs: A Maximum Entropy Approach -- Combining One-Class Classifiers to Classify Missing Data -- Combining Kernel Information for Support Vector Classification -- Combining Classifiers Using Dependency-Based Product Approximation with Bayes Error Rate -- Combining Dissimilarity-Based One-Class Classifiers -- A Modular System for the Classification of Time Series Data -- A Probabilistic Model Using Information Theoretic Measures for Cluster Ensembles -- Classifier Fusion Using Triangular Norms -- Dynamic Integration of Regression Models -- Dynamic Classifier Selection by Adaptive k-Nearest-Neighbourhood Rule -- Design Methods -- Spectral Measure for Multi-class Problems -- The Relationship between Classifier Factorisation and Performance in Stochastic Vector Quantisation -- A Method for Designing Cost-Sensitive ECOC -- Building Graph-Based Classifier Ensembles by Random Node Selection -- A Comparison of Ensemble Creation Techniques -- Multiple Classifiers System for Reducing Influences of Atypical Observations -- Sharing Training Patterns among Multiple Classifiers -- Performance Analysis -- First Experiments on Ensembles of Radial Basis Functions -- Random Aggregated and Bagged Ensembles of SVMs: An Empirical Bias–Variance Analysis -- Building Diverse Classifier Outputs to Evaluate the Behavior of Combination Methods: The Case of TwoClassifiers -- An Empirical Comparison of Hierarchical vs. Two-Level Approaches to Multiclass Problems -- Experiments on Ensembles with Missing and Noisy Data -- Applications -- Induced Decision Fusion in Automated Sign Language Interpretation: Using ICA to Isolate the Underlying Components of Sign -- Ensembles of Classifiers Derived from Multiple Prototypes and Their Application to Handwriting Recognition -- Network Intrusion Detection by a Multi-stage Classification System -- Application of Breiman’s Random Forest to Modeling Structure-Activity Relationships of Pharmaceutical Molecules -- Experimental Study on Multiple LDA Classifier Combination for High Dimensional Data Classification -- Physics-Based Decorrelation of Image Data for Decision Level Fusion in Face Verification -- High Security Fingerprint Verification by Perceptron-Based Fusion of Multiple Matchers -- Second Guessing a Commercial’Black Box’ Classifier by an’In House’ Classifier: Serial Classifier Combination in a Speech Recognition Application.
520 ## - SUMMARY, ETC.
Summary, etc The fusion of di?erent information sourcesis a persistent and intriguing issue. It hasbeenaddressedforcenturiesinvariousdisciplines,includingpoliticalscience, probability and statistics, system reliability assessment, computer science, and distributed detection in communications. Early seminal work on fusion was c- ried out by pioneers such as Laplace and von Neumann. More recently, research activities in information fusion have focused on pattern recognition. During the 1990s,classi?erfusionschemes,especiallyattheso-calleddecision-level,emerged under a plethora of di?erent names in various scienti?c communities, including machine learning, neural networks, pattern recognition, and statistics. The d- ferent nomenclatures introduced by these communities re?ected their di?erent perspectives and cultural backgrounds as well as the absence of common forums and the poor dissemination of the most important results. In 1999, the ?rst workshop on multiple classi?er systems was organized with the main goal of creating a common international forum to promote the diss- ination of the results achieved in the diverse communities and the adoption of a common terminology, thus giving the di?erent perspectives and cultural ba- grounds some concrete added value. After ?ve meetings of this workshop, there is strong evidence that signi?cant steps have been made towards this goal. - searchers from these diverse communities successfully participated in the wo- shops, and world experts presented surveys of the state of the art from the perspectives of their communities to aid cross-fertilization.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Pattern recognition systems.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer vision.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Automated Pattern Recognition.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Vision.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Theory of Computation.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Roli, Fabio.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Kittler, Josef.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Windeatt, Terry.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783540221449
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783662202890
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Lecture Notes in Computer Science,
-- 1611-3349 ;
Volume number/sequential designation 3077
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/b98227">https://doi.org/10.1007/b98227</a>
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Koha item type eBooks-CSE-Springer

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