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1
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Classifier Ensembles for Changing Environments
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16
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A Generic Sensor Fusion Problem: Classification and Function Estimation
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31
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AveBoost2: Boosting for Noisy Data
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41
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Bagging Decision Multi-trees
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52
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Learn++.MT: A New Approach to Incremental Learning
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62
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Beyond Boosting: Recursive ECOC Learning Machines
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72
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Exact Bagging with <Emphasis Type="Italic">k</Emphasis>-Nearest Neighbour Classifiers
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82
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Yet Another Method for Combining Classifiers Outputs: A Maximum Entropy Approach
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92
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Combining One-Class Classifiers to Classify Missing Data
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102
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Combining Kernel Information for Support Vector Classification
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112
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Combining Classifiers Using Dependency-Based Product Approximation with Bayes Error Rate
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122
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Combining Dissimilarity-Based One-Class Classifiers
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134
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A Modular System for the Classification of Time Series Data
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144
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A Probabilistic Model Using Information Theoretic Measures for Cluster Ensembles
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154
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Classifier Fusion Using Triangular Norms
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164
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Dynamic Integration of Regression Models
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174
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Dynamic Classifier Selection by Adaptive k-Nearest-Neighbourhood Rule
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184
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Spectral Measure for Multi-class Problems
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194
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The Relationship between Classifier Factorisation and Performance in Stochastic Vector Quantisation
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204
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A Method for Designing Cost-Sensitive ECOC
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214
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Building Graph-Based Classifier Ensembles by Random Node Selection
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223
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A Comparison of Ensemble Creation Techniques
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233
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Multiple Classifiers System for Reducing Influences of Atypical Observations
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243
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Sharing Training Patterns among Multiple Classifiers
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253
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First Experiments on Ensembles of Radial Basis Functions
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263
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Random Aggregated and Bagged Ensembles of SVMs: An Empirical Bias–Variance Analysis
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273
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Building Diverse Classifier Outputs to Evaluate the Behavior of Combination Methods: The Case of Two Classifiers
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283
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An Empirical Comparison of Hierarchical vs. Two-Level Approaches to Multiclass Problems
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293
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Experiments on Ensembles with Missing and Noisy Data
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303
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Induced Decision Fusion in Automated Sign Language Interpretation: Using ICA to Isolate the Underlying Components of Sign
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314
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Ensembles of Classifiers Derived from Multiple Prototypes and Their Application to Handwriting Recognition
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324
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Network Intrusion Detection by a Multi-stage Classification System
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334
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Application of Breiman’s Random Forest to Modeling Structure-Activity Relationships of Pharmaceutical Molecules
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344
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Experimental Study on Multiple LDA Classifier Combination for High Dimensional Data Classification
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354
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Physics-Based Decorrelation of Image Data for Decision Level Fusion in Face Verification
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364
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High Security Fingerprint Verification by Perceptron-Based Fusion of Multiple Matchers
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374
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Second Guessing a Commercial’Black Box’ Classifier by an’In House’ Classifier: Serial Classifier Combination in a Speech Recognition Application
