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Multiple Classifier Systems [[electronic resource] ] : 12th International Workshop, MCS 2015, Günzburg, Germany, June 29 - July 1, 2015, Proceedings / / edited by Friedhelm Schwenker, Fabio Roli, Josef Kittler
| Multiple Classifier Systems [[electronic resource] ] : 12th International Workshop, MCS 2015, Günzburg, Germany, June 29 - July 1, 2015, Proceedings / / edited by Friedhelm Schwenker, Fabio Roli, Josef Kittler |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (X, 231 p. 40 illus.) |
| Disciplina | 006.31 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Ensemble learning (Machine learning)
Data mining Pattern recognition Optical data processing Information storage and retrieval Data Mining and Knowledge Discovery Pattern Recognition Image Processing and Computer Vision Information Storage and Retrieval |
| ISBN | 3-319-20248-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Novel Bagging Ensemble Approach for Variable Ranking and Selection for Linear Regression Models -- A Hierarchical Ensemble Method for DAG-Structured Taxonomies -- Diversity Measures and Margin Criteria in Multi-class Majority Vote Ensemble -- Fractional Programming Weighted Decoding for Error-Correcting Output Codes -- Instance-Based Decompositions of Error Correcting Output Codes -- Pruning Bagging Ensembles with Metalearning -- Multi-label Selective Ensemble -- Supervised Selective Combination of Diverse Object-Representation Modalities for Regression Estimation -- Detecting Ordinal Class Structures -- Calibrating AdaBoost for Asymmetric Learning -- Building Classifier Ensembles Using Greedy Graph Edit Distance -- Measuring the Stability of Feature Selection with Applications to Ensemble Methods -- Suboptimal Graph Edit Distance Based on Sorted Local Assignments -- Multimodal PLSA for Movie Genre Classification -- One-and-a-Half-Class Multiple Classifier Systems for Secure Learning Against Evasion Attacks at Test Time -- An Experimental Study on Combining Binarization Techniques and Ensemble Methods of Decision Trees -- Decision Tree-Based Multiple Classifier Systems: An FPGA Perspective -- An Empirical Investigation on the Use of Diversity for Creation of Classifier Ensembles -- Bio-Visual Fusion for Person Independent Recognition of Pain Intensity. |
| Record Nr. | UNISA-996198517403316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Multiple Classifier Systems : 12th International Workshop, MCS 2015, Günzburg, Germany, June 29 - July 1, 2015, Proceedings / / edited by Friedhelm Schwenker, Fabio Roli, Josef Kittler
| Multiple Classifier Systems : 12th International Workshop, MCS 2015, Günzburg, Germany, June 29 - July 1, 2015, Proceedings / / edited by Friedhelm Schwenker, Fabio Roli, Josef Kittler |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (X, 231 p. 40 illus.) |
| Disciplina | 006.31 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Ensemble learning (Machine learning)
Data mining Pattern recognition Optical data processing Information storage and retrieval Data Mining and Knowledge Discovery Pattern Recognition Image Processing and Computer Vision Information Storage and Retrieval |
| ISBN | 3-319-20248-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Novel Bagging Ensemble Approach for Variable Ranking and Selection for Linear Regression Models -- A Hierarchical Ensemble Method for DAG-Structured Taxonomies -- Diversity Measures and Margin Criteria in Multi-class Majority Vote Ensemble -- Fractional Programming Weighted Decoding for Error-Correcting Output Codes -- Instance-Based Decompositions of Error Correcting Output Codes -- Pruning Bagging Ensembles with Metalearning -- Multi-label Selective Ensemble -- Supervised Selective Combination of Diverse Object-Representation Modalities for Regression Estimation -- Detecting Ordinal Class Structures -- Calibrating AdaBoost for Asymmetric Learning -- Building Classifier Ensembles Using Greedy Graph Edit Distance -- Measuring the Stability of Feature Selection with Applications to Ensemble Methods -- Suboptimal Graph Edit Distance Based on Sorted Local Assignments -- Multimodal PLSA for Movie Genre Classification -- One-and-a-Half-Class Multiple Classifier Systems for Secure Learning Against Evasion Attacks at Test Time -- An Experimental Study on Combining Binarization Techniques and Ensemble Methods of Decision Trees -- Decision Tree-Based Multiple Classifier Systems: An FPGA Perspective -- An Empirical Investigation on the Use of Diversity for Creation of Classifier Ensembles -- Bio-Visual Fusion for Person Independent Recognition of Pain Intensity. |
| Record Nr. | UNINA-9910483006003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multiple Classifier Systems [[electronic resource] ] : 4th International Workshop, MCS 2003, Guilford, UK, June 11-13, 2003, Proceedings / / edited by Terry Windeatt, Fabio Roli
| Multiple Classifier Systems [[electronic resource] ] : 4th International Workshop, MCS 2003, Guilford, UK, June 11-13, 2003, Proceedings / / edited by Terry Windeatt, Fabio Roli |
| Edizione | [1st ed. 2003.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 |
| Descrizione fisica | 1 online resource (X, 414 p.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Ensemble learning (Machine learning)
Computer industry Pattern recognition Computers Artificial intelligence Optical data processing The Computer Industry Pattern Recognition Computation by Abstract Devices Artificial Intelligence Image Processing and Computer Vision |
| ISBN | 3-540-44938-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. |
| Record Nr. | UNISA-996466156503316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Multiple Classifier Systems : 4th International Workshop, MCS 2003, Guilford, UK, June 11-13, 2003, Proceedings / / edited by Terry Windeatt, Fabio Roli
| Multiple Classifier Systems : 4th International Workshop, MCS 2003, Guilford, UK, June 11-13, 2003, Proceedings / / edited by Terry Windeatt, Fabio Roli |
| Edizione | [1st ed. 2003.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 |
| Descrizione fisica | 1 online resource (X, 414 p.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Ensemble learning (Machine learning)
Computer industry Pattern recognition Computers Artificial intelligence Optical data processing The Computer Industry Pattern Recognition Computation by Abstract Devices Artificial Intelligence Image Processing and Computer Vision |
| ISBN | 3-540-44938-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. |
| Record Nr. | UNINA-9910767537903321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multiple Classifier Systems [[electronic resource] ] : Third International Workshop, MCS 2002, Cagliari, Italy, June 24-26, 2002. Proceedings / / edited by Fabio Roli, Josef Kittler
| Multiple Classifier Systems [[electronic resource] ] : Third International Workshop, MCS 2002, Cagliari, Italy, June 24-26, 2002. Proceedings / / edited by Fabio Roli, Josef Kittler |
| Edizione | [1st ed. 2002.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2002 |
| Descrizione fisica | 1 online resource (X, 342 p.) |
| Disciplina | 006.3/1 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Ensemble learning (Machine learning)
Computer engineering Artificial intelligence Pattern recognition Optical data processing Algorithms Computer Engineering Artificial Intelligence Pattern Recognition Image Processing and Computer Vision Algorithm Analysis and Problem Complexity |
| ISBN | 3-540-45428-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Multiclassifier Systems: Back to the Future -- Support Vector Machines, Kernel Logistic Regression and Boosting -- Multiple Classification Systems in the Context of Feature Extraction and Selection -- Bagging and Boosting -- Boosted Tree Ensembles for Solving Multiclass Problems -- Distributed Pasting of Small Votes -- Bagging and Boosting for the Nearest Mean Classifier: Effects of Sample Size on Diversity and Accuracy -- Highlighting Hard Patterns via AdaBoost Weights Evolution -- Using Diversity with Three Variants of Boosting: Aggressive, Conservative, and Inverse -- Ensemble Learning and Neural Networks -- Multistage Neural Network Ensembles -- Forward and Backward Selection in Regression Hybrid Network -- Types of Multinet System -- Discriminant Analysis and Factorial Multiple Splits in Recursive Partitioning for Data Mining -- Design Methodologies -- New Measure of Classifier Dependency in Multiple Classifier Systems -- A Discussion on the Classifier Projection Space for Classifier Combining -- On the General Application of the Tomographic Classifier Fusion Methodology -- Post-processing of Classifier Outputs in Multiple Classifier Systems -- Combination Strategies -- Trainable Multiple Classifier Schemes for Handwritten Character Recognition -- Generating Classifier Ensembles from Multiple Prototypes and Its Application to Handwriting Recognition -- Adaptive Feature Spaces for Land Cover Classification with Limited Ground Truth Data -- Stacking with Multi-response Model Trees -- On Combining One-Class Classifiers for Image Database Retrieval -- Analysis and Performance Evaluation -- Bias—Variance Analysis and Ensembles of SVM -- An Experimental Comparison of Fixed and Trained Fusion Rules for Crisp Classifier Outputs -- Reduction of the Boasting Bias of Linear Experts -- Analysis of Linear and Order Statistics Combiners for Fusion of Imbalanced Classifiers -- Applications -- Boosting and Classification of Electronic Nose Data -- Content-Based Classification of Digital Photos -- Classifier Combination for In Vivo Magnetic Resonance Spectra of Brain Tumours -- Combining Classifiers of Pesticides Toxicity through a Neuro-fuzzy Approach -- A Multi-expert System for Movie Segmentation -- Decision Level Fusion of Intramodal Personal Identity Verification Experts -- An Experimental Comparison of Classifier Fusion Rules for Multimodal Personal Identity Verification Systems. |
| Record Nr. | UNISA-996465540803316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Multiple Classifier Systems : Third International Workshop, MCS 2002, Cagliari, Italy, June 24-26, 2002. Proceedings / / edited by Fabio Roli, Josef Kittler
| Multiple Classifier Systems : Third International Workshop, MCS 2002, Cagliari, Italy, June 24-26, 2002. Proceedings / / edited by Fabio Roli, Josef Kittler |
| Edizione | [1st ed. 2002.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2002 |
| Descrizione fisica | 1 online resource (X, 342 p.) |
| Disciplina | 006.3/1 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Ensemble learning (Machine learning)
Computer engineering Artificial intelligence Pattern recognition Optical data processing Algorithms Computer Engineering Artificial Intelligence Pattern Recognition Image Processing and Computer Vision Algorithm Analysis and Problem Complexity |
| ISBN | 3-540-45428-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Multiclassifier Systems: Back to the Future -- Support Vector Machines, Kernel Logistic Regression and Boosting -- Multiple Classification Systems in the Context of Feature Extraction and Selection -- Bagging and Boosting -- Boosted Tree Ensembles for Solving Multiclass Problems -- Distributed Pasting of Small Votes -- Bagging and Boosting for the Nearest Mean Classifier: Effects of Sample Size on Diversity and Accuracy -- Highlighting Hard Patterns via AdaBoost Weights Evolution -- Using Diversity with Three Variants of Boosting: Aggressive, Conservative, and Inverse -- Ensemble Learning and Neural Networks -- Multistage Neural Network Ensembles -- Forward and Backward Selection in Regression Hybrid Network -- Types of Multinet System -- Discriminant Analysis and Factorial Multiple Splits in Recursive Partitioning for Data Mining -- Design Methodologies -- New Measure of Classifier Dependency in Multiple Classifier Systems -- A Discussion on the Classifier Projection Space for Classifier Combining -- On the General Application of the Tomographic Classifier Fusion Methodology -- Post-processing of Classifier Outputs in Multiple Classifier Systems -- Combination Strategies -- Trainable Multiple Classifier Schemes for Handwritten Character Recognition -- Generating Classifier Ensembles from Multiple Prototypes and Its Application to Handwriting Recognition -- Adaptive Feature Spaces for Land Cover Classification with Limited Ground Truth Data -- Stacking with Multi-response Model Trees -- On Combining One-Class Classifiers for Image Database Retrieval -- Analysis and Performance Evaluation -- Bias—Variance Analysis and Ensembles of SVM -- An Experimental Comparison of Fixed and Trained Fusion Rules for Crisp Classifier Outputs -- Reduction of the Boasting Bias of Linear Experts -- Analysis of Linear and Order Statistics Combiners for Fusion of Imbalanced Classifiers -- Applications -- Boosting and Classification of Electronic Nose Data -- Content-Based Classification of Digital Photos -- Classifier Combination for In Vivo Magnetic Resonance Spectra of Brain Tumours -- Combining Classifiers of Pesticides Toxicity through a Neuro-fuzzy Approach -- A Multi-expert System for Movie Segmentation -- Decision Level Fusion of Intramodal Personal Identity Verification Experts -- An Experimental Comparison of Classifier Fusion Rules for Multimodal Personal Identity Verification Systems. |
| Record Nr. | UNINA-9910143901403321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multiple Classifier Systems [[electronic resource] ] : Second International Workshop, MCS 2001 Cambridge, UK, July 2-4, 2001 Proceedings / / edited by Josef Kittler, Fabio Roli
| Multiple Classifier Systems [[electronic resource] ] : Second International Workshop, MCS 2001 Cambridge, UK, July 2-4, 2001 Proceedings / / edited by Josef Kittler, Fabio Roli |
| Edizione | [1st ed. 2001.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 |
| Descrizione fisica | 1 online resource (XII, 456 p.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Pattern recognition Optical data processing Computers Algorithms Ensemble learning (Machine learning) Artificial Intelligence Pattern Recognition Image Processing and Computer Vision Computation by Abstract Devices Algorithm Analysis and Problem Complexity |
| ISBN | 3-540-48219-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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: Decorrelation through Dimensionality Reduction -- Classifier Combination as a Tomographic Process -- MCS in Remote Sensing -- A Robust Multiple Classifier System for a Partially Unsupervised Updating of Land-Cover Maps -- Combining Supervised Remote Sensing Image Classifiers Based on Individual Class Performances -- Boosting, Bagging, and Consensus Based Classification of Multisource Remote Sensing Data -- Solar Wind Data Analysis Using Self-Organizing Hierarchical Neural Network Classifiers -- One Class MCS and Clustering -- Combining One-Class Classifiers -- Finding Consistent Clusters in Data Partitions -- A Self-Organising Approach to Multiple Classifier Fusion -- Combination Strategies -- Error Rejection in Linearly Combined Multiple Classifiers -- Relationship of Sum and Vote Fusion Strategies -- Complexity of Data Subsets Generated by the Random Subspace Method: An Experimental Investigation -- On Combining Dissimilarity Representations -- Application of Multiple Classifier Techniques to Subband Speaker Identification with an HMM/ANN System -- Classification of Time Series Utilizing Temporal and Decision Fusion -- Use of Positional Information in Sequence Alignment for Multiple Classifier Combination -- Application of the Evolutionary Algorithms for Classifier Selection in Multiple Classifier Systems with Majority Voting -- Tree-Structured Support Vector Machines for Multi-class Pattern Recognition -- On the Combination of Different Template Matching Strategies for Fast Face Detection -- Improving Product by Moderating k-NN Classifiers -- Automatic Model Selection in a Hybrid Perceptron/Radial Network. |
| Record Nr. | UNISA-996465816503316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Multiple Classifier Systems : Second International Workshop, MCS 2001 Cambridge, UK, July 2-4, 2001 Proceedings / / edited by Josef Kittler, Fabio Roli
| Multiple Classifier Systems : Second International Workshop, MCS 2001 Cambridge, UK, July 2-4, 2001 Proceedings / / edited by Josef Kittler, Fabio Roli |
| Edizione | [1st ed. 2001.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 |
| Descrizione fisica | 1 online resource (XII, 456 p.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Pattern recognition Optical data processing Computers Algorithms Ensemble learning (Machine learning) Artificial Intelligence Pattern Recognition Image Processing and Computer Vision Computation by Abstract Devices Algorithm Analysis and Problem Complexity |
| ISBN | 3-540-48219-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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: Decorrelation through Dimensionality Reduction -- Classifier Combination as a Tomographic Process -- MCS in Remote Sensing -- A Robust Multiple Classifier System for a Partially Unsupervised Updating of Land-Cover Maps -- Combining Supervised Remote Sensing Image Classifiers Based on Individual Class Performances -- Boosting, Bagging, and Consensus Based Classification of Multisource Remote Sensing Data -- Solar Wind Data Analysis Using Self-Organizing Hierarchical Neural Network Classifiers -- One Class MCS and Clustering -- Combining One-Class Classifiers -- Finding Consistent Clusters in Data Partitions -- A Self-Organising Approach to Multiple Classifier Fusion -- Combination Strategies -- Error Rejection in Linearly Combined Multiple Classifiers -- Relationship of Sum and Vote Fusion Strategies -- Complexity of Data Subsets Generated by the Random Subspace Method: An Experimental Investigation -- On Combining Dissimilarity Representations -- Application of Multiple Classifier Techniques to Subband Speaker Identification with an HMM/ANN System -- Classification of Time Series Utilizing Temporal and Decision Fusion -- Use of Positional Information in Sequence Alignment for Multiple Classifier Combination -- Application of the Evolutionary Algorithms for Classifier Selection in Multiple Classifier Systems with Majority Voting -- Tree-Structured Support Vector Machines for Multi-class Pattern Recognition -- On the Combination of Different Template Matching Strategies for Fast Face Detection -- Improving Product by Moderating k-NN Classifiers -- Automatic Model Selection in a Hybrid Perceptron/Radial Network. |
| Record Nr. | UNINA-9910143595003321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multiple Classifier Systems [[electronic resource] ] : First International Workshop, MCS 2000 Cagliari, Italy, June 21-23, 2000 Proceedings / / edited by Josef Kittler, Fabio Roli
| Multiple Classifier Systems [[electronic resource] ] : First International Workshop, MCS 2000 Cagliari, Italy, June 21-23, 2000 Proceedings / / edited by Josef Kittler, Fabio Roli |
| Edizione | [1st ed. 2000.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2000 |
| Descrizione fisica | 1 online resource (XII, 408 p.) |
| Disciplina | 006.3/1 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Ensemble learning (Machine learning)
Pattern recognition Artificial intelligence Optical data processing Algorithms Computers Pattern Recognition Artificial Intelligence Image Processing and Computer Vision Algorithm Analysis and Problem Complexity Computation by Abstract Devices |
| ISBN | 3-540-45014-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Ensemble Methods in Machine Learning -- Experiments with Classifier Combining Rules -- The “Test and Select” Approach to Ensemble Combination -- A Survey of Sequential Combination of Word Recognizers in Handwritten Phrase Recognition at CEDAR -- Multiple Classifier Combination Methodologies for Different Output Levels -- A Mathematically Rigorous Foundation for Supervised Learning -- Classifier Combinations: Implementations and Theoretical Issues -- Some Results on Weakly Accurate Base Learners for Boosting Regression and Classification -- Complexity of Classification Problems and Comparative Advantages of Combined Classifiers -- Effectiveness of Error Correcting Output Codes in Multiclass Learning Problems -- Combining Fisher Linear Discriminants for Dissimilarity Representations -- A Learning Method of Feature Selection for Rough Classification -- Analysis of a Fusion Method for Combining Marginal Classifiers -- A hybrid projection based and radial basis function architecture -- Combining Multiple Classifiers in Probabilistic Neural Networks -- Supervised Classifier Combination through Generalized Additive Multi-model -- Dynamic Classifier Selection -- Boosting in Linear Discriminant Analysis -- Different Ways of Weakening Decision Trees and Their Impact on Classification Accuracy of DT Combination -- Applying Boosting to Similarity Literals for Time Series Classification -- Boosting of Tree-Based Classifiers for Predictive Risk Modeling in GIS -- A New Evaluation Method for Expert Combination in Multi-expert System Designing -- Diversity between Neural Networks and Decision Trees for Building Multiple Classifier Systems -- Self-Organizing Decomposition of Functions -- Classifier Instability and Partitioning -- A Hierarchical Multiclassifier System for Hyperspectral Data Analysis -- Consensus Based Classification of Multisource Remote Sensing Data -- Combining Parametric and Nonparametric Classifiers for an Unsupervised Updating of Land-Cover Maps -- A Multiple Self-Organizing Map Scheme for Remote Sensing Classification -- Use of Lexicon Density in Evaluating Word Recognizers -- A Multi-expert System for Dynamic Signature Verification -- A Cascaded Multiple Expert System for Verification -- Architecture for Classifier Combination Using Entropy Measures -- Combining Fingerprint Classifiers -- Statistical Sensor Calibration for Fusion of Different Classifiers in a Biometric Person Recognition Framework -- A Modular Neuro-Fuzzy Network for Musical Instruments Classification -- Classifier Combination for Grammar-Guided Sentence Recognition -- Shape Matching and Extraction by an Array of Figure-and-Ground Classifiers. |
| Record Nr. | UNISA-996465562403316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2000 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Multiple Classifier Systems : First International Workshop, MCS 2000 Cagliari, Italy, June 21-23, 2000 Proceedings / / edited by Josef Kittler, Fabio Roli
| Multiple Classifier Systems : First International Workshop, MCS 2000 Cagliari, Italy, June 21-23, 2000 Proceedings / / edited by Josef Kittler, Fabio Roli |
| Edizione | [1st ed. 2000.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2000 |
| Descrizione fisica | 1 online resource (XII, 408 p.) |
| Disciplina | 006.3/1 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Ensemble learning (Machine learning)
Pattern recognition Artificial intelligence Optical data processing Algorithms Computers Pattern Recognition Artificial Intelligence Image Processing and Computer Vision Algorithm Analysis and Problem Complexity Computation by Abstract Devices |
| ISBN | 3-540-45014-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Ensemble Methods in Machine Learning -- Experiments with Classifier Combining Rules -- The “Test and Select” Approach to Ensemble Combination -- A Survey of Sequential Combination of Word Recognizers in Handwritten Phrase Recognition at CEDAR -- Multiple Classifier Combination Methodologies for Different Output Levels -- A Mathematically Rigorous Foundation for Supervised Learning -- Classifier Combinations: Implementations and Theoretical Issues -- Some Results on Weakly Accurate Base Learners for Boosting Regression and Classification -- Complexity of Classification Problems and Comparative Advantages of Combined Classifiers -- Effectiveness of Error Correcting Output Codes in Multiclass Learning Problems -- Combining Fisher Linear Discriminants for Dissimilarity Representations -- A Learning Method of Feature Selection for Rough Classification -- Analysis of a Fusion Method for Combining Marginal Classifiers -- A hybrid projection based and radial basis function architecture -- Combining Multiple Classifiers in Probabilistic Neural Networks -- Supervised Classifier Combination through Generalized Additive Multi-model -- Dynamic Classifier Selection -- Boosting in Linear Discriminant Analysis -- Different Ways of Weakening Decision Trees and Their Impact on Classification Accuracy of DT Combination -- Applying Boosting to Similarity Literals for Time Series Classification -- Boosting of Tree-Based Classifiers for Predictive Risk Modeling in GIS -- A New Evaluation Method for Expert Combination in Multi-expert System Designing -- Diversity between Neural Networks and Decision Trees for Building Multiple Classifier Systems -- Self-Organizing Decomposition of Functions -- Classifier Instability and Partitioning -- A Hierarchical Multiclassifier System for Hyperspectral Data Analysis -- Consensus Based Classification of Multisource Remote Sensing Data -- Combining Parametric and Nonparametric Classifiers for an Unsupervised Updating of Land-Cover Maps -- A Multiple Self-Organizing Map Scheme for Remote Sensing Classification -- Use of Lexicon Density in Evaluating Word Recognizers -- A Multi-expert System for Dynamic Signature Verification -- A Cascaded Multiple Expert System for Verification -- Architecture for Classifier Combination Using Entropy Measures -- Combining Fingerprint Classifiers -- Statistical Sensor Calibration for Fusion of Different Classifiers in a Biometric Person Recognition Framework -- A Modular Neuro-Fuzzy Network for Musical Instruments Classification -- Classifier Combination for Grammar-Guided Sentence Recognition -- Shape Matching and Extraction by an Array of Figure-and-Ground Classifiers. |
| Record Nr. | UNINA-9910767550803321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2000 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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