多分类器系统Multiple classifier systems( 多级分类器系统 )

多分类器系统Multiple classifier systems( 多级分类器系统 )

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作者: Josef Kittler 著

出版社: 湖南文艺出版社

出版时间: 2001-12

版次: 1

ISBN: 9783540422846

定价: 654.84

装帧: 平装

开本: 其他

纸张: 胶版纸

页数: 456页

分类: 计算机与互联网

　　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.

Proceedings of the Second Intl Workshop on Multiple Classifier Systems, MCS 2001, held in Cambridge, UK, in July 2001. Softcover. Bagging and Boosting

　Bagging and the Random Subspace Method for Redundant Feature Spaces

　Performance Degradation in Boosting

　A Generalized Class of Boosting Algorithms Based on Recursive Decoding Models

　Tuning Cost-Sensitive Boosting and Its Application to Melanoma Diagnosis

　Learning Classification RBF Networks by Boosting

MCS Design Methodology

　Data Complexity Analysis for Classifier Combination

　Genetic Programming for Improved Receiver Operating Characteristics

　Methods for Designing Multiple Classifier Systems

　Decision-Level Fusion in Fingerprint Verification

　Genetic Algorithms for Multi-classifier System Configuration: A Case Study in Character Recognition

　Combined Classification of Handwritten Digits Using the 'Virtual Test Sample Method' .

　Averaging Weak Classifiers

　Mixing a Symbolic and a Subsymbolic Expert to Improve Carcinogenicity Prediction of Aromatic Compounds

　Ensemble Classifiers

　Multiple Classifier Systems Based on Interpretable Linear Classifiers

　Least Squares and Estimation Measures via Error Correcting Output Code

　Dependence among Codeword Bits Errors in ECOC Learning Machines An Experimental Analysis

　Information Analysis of Multiple Classifier Fusion

　Limiting the Number of Trees in Random Forests

　Learning-Data Selection Mechanism through Neural Networks Ensemble

　A Multi-SVM Classification System

　Automatic Classification of Clustered Microcalcifications by a Multiple Classifier System

　Feature Spaces for MCS

　Feature Weighted Ensemble Classifiers - A Modified Decision Scheme

　Feature Subsets for Classifier Combination: An Enumerative Experiment

　Input Decimation Ensembles: Decorrelating through Dimensionality Reduction

　Classifier Combination as a Tomographic Process

MCS in Remote Sensing

One Class MCS and Clustering

Combination Strategies

Author Index
内容简介:
　　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.

Proceedings of the Second Intl Workshop on Multiple Classifier Systems, MCS 2001, held in Cambridge, UK, in July 2001. Softcover.
目录:
Bagging and Boosting

　Bagging and the Random Subspace Method for Redundant Feature Spaces

　Performance Degradation in Boosting

　A Generalized Class of Boosting Algorithms Based on Recursive Decoding Models

　Tuning Cost-Sensitive Boosting and Its Application to Melanoma Diagnosis

　Learning Classification RBF Networks by Boosting

MCS Design Methodology

　Data Complexity Analysis for Classifier Combination

　Genetic Programming for Improved Receiver Operating Characteristics

　Methods for Designing Multiple Classifier Systems

　Decision-Level Fusion in Fingerprint Verification

　Genetic Algorithms for Multi-classifier System Configuration: A Case Study in Character Recognition

　Combined Classification of Handwritten Digits Using the 'Virtual Test Sample Method' .

　Averaging Weak Classifiers

　Mixing a Symbolic and a Subsymbolic Expert to Improve Carcinogenicity Prediction of Aromatic Compounds

　Ensemble Classifiers

　Multiple Classifier Systems Based on Interpretable Linear Classifiers

　Least Squares and Estimation Measures via Error Correcting Output Code

　Dependence among Codeword Bits Errors in ECOC Learning Machines An Experimental Analysis

　Information Analysis of Multiple Classifier Fusion

　Limiting the Number of Trees in Random Forests

　Learning-Data Selection Mechanism through Neural Networks Ensemble

　A Multi-SVM Classification System

　Automatic Classification of Clustered Microcalcifications by a Multiple Classifier System

　Feature Spaces for MCS

　Feature Weighted Ensemble Classifiers - A Modified Decision Scheme

　Feature Subsets for Classifier Combination: An Enumerative Experiment

　Input Decimation Ensembles: Decorrelating through Dimensionality Reduction

　Classifier Combination as a Tomographic Process

MCS in Remote Sensing

One Class MCS and Clustering

Combination Strategies

Author Index

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