Multiple Classifier Systems (Record no. 188968)

MARC details
000 -LEADER
fixed length control field 06085nam a22006135i 4500
001 - CONTROL NUMBER
control field 978-3-540-44938-6
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423132539.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 121227s2003 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783540449386
-- 978-3-540-44938-6
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/3-540-44938-8
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number HD9696.2-9696.82
072 #7 - SUBJECT CATEGORY CODE
Subject category code KNTX
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code BUS070030
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code KNTX
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 338.47004
Edition number 23
245 10 - TITLE STATEMENT
Title Multiple Classifier Systems
Medium [electronic resource] :
Remainder of title 4th International Workshop, MCS 2003, Guilford, UK, June 11-13, 2003, Proceedings /
Statement of responsibility, etc edited by Terry Windeatt, Fabio Roli.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2003.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2003.
300 ## - PHYSICAL DESCRIPTION
Extent X, 414 p.
Other physical details online resource.
336 ## -
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-- computer
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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 2709
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Invited Paper -- Data Dependence in Combining Classifiers -- Boosting -- Boosting with Averaged Weight Vectors -- Error Bounds for Aggressive and Conservative AdaBoost -- An Empirical Comparison of Three Boosting Algorithms on Real Data Sets with Artificial Class Noise -- The Beneficial Effects of Using Multi-net Systems That Focus on Hard Patterns -- Combination Rules -- The Behavior Knowledge Space Fusion Method: Analysis of Generalization Error and Strategies for Performance Improvement -- Reducing the Overconfidence of Base Classifiers when Combining Their Decisions -- Linear Combiners for Classifier Fusion: Some Theoretical and Experimental Results -- Comparison of Classifier Selection Methods for Improving Committee Performance -- Towards Automated Classifier Combination for Pattern Recognition -- Multi-class Methods -- Serial Multiple Classifier Systems Exploiting a Coarse to Fine Output Coding -- Polychotomous Classification with Pairwise Classifiers: A New Voting Principle -- Multi-category Classification by Soft-Max Combination of Binary Classifiers -- A Sequential Scheduling Approach to Combining Multiple Object Classifiers Using Cross-Entropy -- Binary Classifier Fusion Based on the Basic Decomposition Methods -- Fusion Schemes Architectures -- Good Error Correcting Output Codes for Adaptive Multiclass Learning -- Finding Natural Clusters Using Multi-clusterer Combiner Based on Shared Nearest Neighbors -- An Ensemble Approach for Data Fusion with Learn++ -- The Practical Performance Characteristics of Tomographically Filtered Multiple Classifier Fusion -- Accumulated-Recognition-Rate Normalization for Combining Multiple On/Off-Line Japanese Character Classifiers Tested on a Large Database -- Beam Search Extraction and Forgetting Strategies on Shared Ensembles -- A Markov Chain Approach to Multiple Classifier Fusion -- Neural Network Ensembles -- A Study of Ensemble of Hybrid Networks with Strong Regularization -- Combining Multiple Modes of Information Using Unsupervised Neural Classifiers -- Neural Net Ensembles for Lithology Recognition -- Improving Performance of a Multiple Classifier System Using Self-generating Neural Networks -- Ensemble Strategies -- Negative Correlation Learning and the Ambiguity Family of Ensemble Methods -- Spectral Coefficients and Classifier Correlation -- Ensemble Construction via Designed Output Distortion -- Simulating Classifier Outputs for Evaluating Parallel Combination Methods -- A New Ensemble Diversity Measure Applied to Thinning Ensembles -- Ensemble Methods for Noise Elimination in Classification Problems -- Applications -- New Boosting Algorithms for Classification Problems with Large Number of Classes Applied to a Handwritten Word Recognition Task -- Automatic Target Recognition Using Multiple Description Coding Models for Multiple Classifier Systems -- A Modular Multiple Classifier System for the Detection of Intrusions in Computer Networks -- Input Space Transformations for Multi-classifier Systems Based on n-tuple Classifiers with Application to Handwriting Recognition -- Building Classifier Ensembles for Automatic Sports Classification -- Classification of Aircraft Maneuvers for Fault Detection -- Solving Problems Two at a Time: Classification of Web Pages Using a Generic Pair-Wise Multiple Classifier System -- Design and Evaluation of an Adaptive Combination Framework for OCR Result Strings.
520 ## - SUMMARY, ETC.
Summary, etc This book constitutes the refereed proceedings of the 4th International Workshop on Multiple Classifier Systems, MCS 2003, held in Guildford, UK in June 2003. The 40 revised full papers presented with one invited paper were carefully reviewed and selected for presentation. The papers are organized in topical sections on boosting, combination rules, multi-class methods, fusion schemes and architectures, neural network ensembles, ensemble strategies, and applications.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer industry.
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 science.
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 Computer vision.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element The Computer Industry.
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 Theory of Computation.
650 24 - 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 Computer Vision.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Windeatt, Terry.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Roli, Fabio.
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 9783540403692
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783662197431
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Lecture Notes in Computer Science,
-- 1611-3349 ;
Volume number/sequential designation 2709
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/3-540-44938-8">https://doi.org/10.1007/3-540-44938-8</a>
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks-CSE-Springer

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