Multiple Classifier Systems: Proceedings of the Second International Workshop, McS 2001 Cambridge, Uk, July 2-4, 2001

by Kittler, Josef; Roli, Fabio; International Workshop on Multiple Classifier Systems 2001 Cambridge

• ISBN13: 9783540422846
• ISBN10: 3540422846
• Format: Paperback
• Copyright: 2001-08-01
• Publisher: Springer Verlag

Summary

This book constitutes the refereed proceedings of the Second International Workshop on Multiple Classifier Systems, MCS 2001, held in Cambridge, UK in July 2001.The 44 revised papers presented were carefully reviewed and selected for presentation. The book offers topical sections on bagging and boosting, MCS design methodology, ensemble classifiers, feature spaces for MCS, MCS in remote sensing, one class MCS and clustering, and combination strategies.

Table of Contents

Bagging and Boosting
Bagging and the Random Subspace Method for Redundant Feature Spaces	1	(10)
M. Skurichina
R.P.W. Duin
Performance Degradation in Boosting	11	(11)
J. Wickramaratna
S. Holden
B. Buxton
A Generalized Class of Boosting Algorithms Based on Recursive Decoding Models	22	(10)
E. Tapia
J.C. Gonzalez
J. Villena
Tuning Cost-Sensitive Boosting and Its Application to Melanoma Diagnosis	32	(11)
S. Merler
C. Furlanello
B. Larcher
A. Sboner
Learning Classification RBF Networks by Boosting	43	(10)
J.J. Rodriguez Diez
C.J. Alonso Gonzalez
MCS Design Methodology
Data Complexity Analysis for Classifier Combination	53	(15)
T.K. Ho
Genetic Programming for Improved Receiver Operating Characteristics	68	(10)
W.B. Langdon
B.F. Buxton
Methods for Designing Multiple Classifier Systems	78	(10)
F. Roli
G. Giacinto
and G. Vernazza
Decision-Level Fusion in Fingerprint Verification	88	(11)
S. Prabhakar
A.K. Jain
Genetic Algorithms for Multi-classifier System Configuration: A Case Study in Character Recognition	99	(10)
K. Sirlantzis
M.C. Fairhurst
M.S. Hoque
Combined Classification of Handwritten Digits Using the `Virtual Test Sample Method'	109	(10)
J. Dahmen
D. Keysers
H. Ney
Averaging Weak Classifiers	119	(7)
D. Chen
J. Liu
Mixing a Symbolic and a Subsymbolic Expert to Improve Carcinogenicity Prediction of Aromatic Compounds	126	(10)
G. Gini
M. Lorenzini
E. Benfenati
R. Brambilla
L. Malve
Ensemble Classifiers
Multiple Classifier Systems Based on Interpretable Linear Classifiers	136	(12)
D.J. Hand
N.M. Adams
M.G. Kelly
Least Squares and Estimation Measures via Error Correcting Output Code	148	(10)
R. Ghaderi
T. Windeatt
Dependence among Codeword Bits Errors in ECOC Learning Machines: An Experimental Analysis	158	(10)
F. Masulli
G. Valentini
Information Analysis of Multiple Classifier Fusion	168	(10)
J. Grim
J. Kittler
P. Pudil
P. Somol
Limiting the Number of Trees in Random Forests	178	(10)
P. Latinne
O. Debeir
C. Decaestecker
Learning-Data Selection Mechanism through Neural Networks Ensemble	188	(10)
P. Hartono
S. Hashimoto
A Multi-SVM Classification System	198	(10)
D.S. Frossyniotis
A. Stafylopatis
Automatic Classification of Clustered Microcalcifications by a Multiple Classifier System	208	(10)
P. Foggia
C. Sansone
F. Tortorella
M. Vento
Feature Spaces for MCS
Feature Weighted Ensemble Classifiers-A Modified Decision Scheme	218	(10)
T.M. Jorgensen
C. Linneberg
Feature Subsets for Classifier Combination: An Enumerative Experiment	228	(10)
L.I. Kuncheva
C.J. Whitaker
Input Decimation Ensembles: Decorrelating through Dimensionality Reduction	238	(10)
N.C. Oza
K. Tumer
Classifier Combination as a Tomographic Process	248	(11)
D. Windridge
J. Kittler
MCS in Remote Sensing
A Robust Multiple Classifier System for a Partially Unsupervised Updating of Land-Cover Maps	259	(10)
L. Bruzzone
R. Cossu
Combining Supervised Remote Sensing Image Classifiers Based on Individual Class Performances	269	(10)
P.C. Smits
Boosting, Bagging, and Consensus Based Classification of Multisource Remote Sensing Data	279	(10)
G.J. Briem
J.A. Benediktsson
J.R. Sveinsson
Solar Wind Data Analysis Using Self-Organizing Hierarchical Neural Network Classifiers	289	(10)
S.A. Dolenko
Y.V. Orlov
I.G. Persiantsev
J.S. Shugai
A.V. Dmitriev
A.V. Suvorova
I.S. Veselovsky
One Class MCS and Clustering
Combining One-Class Classifiers	299	(10)
D.M.J. Tax
R.P.W. Duin
Finding Consistent Clusters in Data Partitions	309	(10)
A. Fred
A Self-Organising Approach to Multiple Classifier Fusion	319	(10)
S.P. Luttrell
Combination Strategies
Error Rejection in Linearly Combined Multiple Classifiers	329	(10)
G. Fumera
F. Roli
Relationship of Sum and Vote Fusion Strategies	339	(10)
J. Kittler
F.M. Alkoot
Complexity of Data Subsets Generated by the Random Subspace Method: An Experimental Investigation	349	(10)
L.I. Kuncheva
F. Roli
G.L. Marcialis
C.A. Shipp
On Combining Dissimiliarity Representations	359	(10)
E. Pekalska
R.P.W. Duin
Application of Multiple Classifier Techniques to Subband Speaker Identification with an HMM/ANN System	369	(9)
J.E. Higgins
T.J. Dodd
R.I. Damper
Classification of Time Series Utilizing Temporal and Decision Fusion	378	(10)
C. Dietrich
F. Schwenker
G. Palm
Use of Positional Information in Sequence Alignment for Multiple Classifier Combination	388	(11)
U.-V. Marti
H. Bunke
Application of the Evolutionary Algorithms for Classifier Selection in Multiple Classifier Systems with Majority Voting	399	(10)
D. Ruta
B. Gabrys
Tree Structured Support Vector Machines for Multi-class Pattern Recognition	409	(9)
F. Schwenker
G. Palm
On the Combination of Different Template Matching Strategies for Fast Face Detection	418	(11)
B. Froba
W. Zink
Improving Product by Moderating k-NN Classifiers	429	(11)
F.M. Alkoot
J. Kittler
Automatic Model Selection in a Hybrid Perceptron/Radial Network	440	(15)
S. Cohen
N. Intrator
Author Index	455