The Strength of Weak Learnability
Machine Learning
Training a 3-node neural network is NP-complete
COLT '88 Proceedings of the first annual workshop on Computational learning theory
The cascade-correlation learning architecture
Advances in neural information processing systems 2
Approximation capabilities of multilayer feedforward networks
Neural Networks
Back propagation is sensitive to initial conditions
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Handwritten numerical recognition based on multiple algorithms
Pattern Recognition
Neural networks and the bias/variance dilemma
Neural Computation
C4.5: programs for machine learning
C4.5: programs for machine learning
Genetic algorithm for feature selection for parallel classifiers
Information Processing Letters
Approximation and radial-basis-function networks
Neural Computation
An introduction to Kolmogorov complexity and its applications
An introduction to Kolmogorov complexity and its applications
Combining the results of several neural network classifiers
Neural Networks
Democracy in neural nets: voting schemes for classification
Neural Networks
Hierarchical mixtures of experts and the EM algorithm
Neural Computation
Advances in fuzzy integration for pattern recognition
Fuzzy Sets and Systems - Special issue on fuzzy methods for computer vision and pattern recognition
A Method of Combining Multiple Experts for the Recognition of Unconstrained Handwritten Numerals
IEEE Transactions on Pattern Analysis and Machine Intelligence
Methods for combining experts' probability assessments
Neural Computation
Optimal combinations of pattern classifiers
Pattern Recognition Letters
Boosting a weak learning algorithm by majority
Information and Computation
Machine Learning
Error reduction through learning multiple descriptions
Machine Learning
Combination of Multiple Classifiers Using Local Accuracy Estimates
IEEE Transactions on Pattern Analysis and Machine Intelligence
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
An application of OWA operators to the aggregation of multiple classification decisions
The ordered weighted averaging operators
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Random Subspace Method for Constructing Decision Forests
IEEE Transactions on Pattern Analysis and Machine Intelligence
Training methods for adaptive boosting of neural networks
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Prediction games and arcing algorithms
Neural Computation
Improved Boosting Algorithms Using Confidence-rated Predictions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Improved Generalization Through Explicit Optimization of Margins
Machine Learning
On the Algorithmic Implementation of Stochastic Discrimination
IEEE Transactions on Pattern Analysis and Machine Intelligence
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
An approach to the automatic design of multiple classifier systems
Pattern Recognition Letters - Special issue on machine learning and data mining in pattern recognition
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality
Data Mining and Knowledge Discovery
Proceedings of the First International Workshop on Multiple Classifier Systems
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Proceedings of the Second International Workshop on Multiple Classifier Systems
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Improved Pairwise Coupling Classification with Correcting Classifiers
ECML '98 Proceedings of the 10th European Conference on Machine Learning
On the Decomposition of Polychotomies into Dichotomies
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Using Error-Correcting Codes for Text Classification
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
The ``Test and Select'' Approach to Ensemble Combination
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Experiments with Classifier Combining Rules
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Ensemble Methods in Machine Learning
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Multiple Classifier Combination Methodologies for Different Output Levels
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
A Mathematically Rigorous Foundation for Supervised Learning
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Data Complexity Analysis for Classifier Combination
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Automatic Model Selection in a Hybrid Perceptron/Radial Network
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Dependence among Codeword Bits Errors in ECOC Learning Machines: An Experimental Analysis
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Methods for Designing Multiple Classifier Systems
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Input Decimation Ensembles: Decorrelation through Dimensionality Reduction
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Complexity of Data Subsets Generated by the Random Subspace Method: An Experimental Investigation
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Tuning Cost-Sensitive Boosting and Its Application to Melanoma Diagnosis
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Bagging and the Random Subspace Method for Redundant Feature Spaces
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Feature Subsets for Classifier Combination: An Enumerative Experiment
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Complexity of Classification Problems and Comparative Advantages of Combined Classifiers
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
A Hybrid Projection Based and Radial Basis Function Architecture
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Classifier Combinations: Implementations and Theoretical Issues
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Boosting of Tree-Based Classifiers for Predictive Risk Modeling in GIS
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Effectiveness of Error Correcting Output Codes in Multiclass Learning Problems
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
A New Evaluation Method for Expert Combination in Multi-expert System Designing
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
On the Learnability and Design of Output Codes for Multiclass Problems
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
Boosting, Bagging, and Consensus Based Classification of Multisource Remote Sensing Data
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
Adaptive mixtures of local experts
Neural Computation
Engineering multiversion neural-net systems
Neural Computation
Boosting and other ensemble methods
Neural Computation
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
A brief introduction to boosting
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Use of fuzzy-logic-inspired features to improve bacterialrecognition through classifier fusion
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Application of majority voting to pattern recognition: an analysis of its behavior and performance
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Artificial Intelligence in Medicine
Combinations of weak classifiers
IEEE Transactions on Neural Networks
Parallel consensual neural networks
IEEE Transactions on Neural Networks
Efficient classification for multiclass problems using modular neural networks
IEEE Transactions on Neural Networks
Multiple network fusion using fuzzy logic
IEEE Transactions on Neural Networks
A genetic integrated fuzzy classifier
Pattern Recognition Letters - Special issue: Advances in pattern recognition
Classification by evolutionary ensembles
Pattern Recognition
An integrated fuzzy cells-classifier
Image and Vision Computing
A boosting approach for corporate failure prediction
Applied Intelligence
Constructing ensembles of symbolic classifiers
International Journal of Hybrid Intelligent Systems - Hybrid Intelligent systems in Ensembles
Mapping a specific class with an ensemble of classifiers
International Journal of Remote Sensing
Feature-based classifier ensembles for diagnosing multiple faults in rotating machinery
Applied Soft Computing
Optimized Associative Memories for Feature Selection
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Combining One Class Fuzzy KNN's
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Combining Answers of Sub-classifiers in the Bagging-Feature Ensembles
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Agent-Based Approach to Distributed Ensemble Learning of Fuzzy ARTMAP Classifiers
KES-AMSTA '07 Proceedings of the 1st KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
A PSO Based Adaboost Approach to Object Detection
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
Diversity in Combinations of Heterogeneous Classifiers
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Computational Statistics & Data Analysis
Repairing concavities in ROC curves
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Human-machine interaction issues in quality control based on online image classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A selection approach for scalable fuzzy integral combination
Information Fusion
Towards incremental classifier fusion
Intelligent Data Analysis
Feature Selection with Ensembles, Artificial Variables, and Redundancy Elimination
The Journal of Machine Learning Research
Multi-represented classification based on confidence estimation
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
On combined classifiers, rule induction and rough sets
Transactions on rough sets VI
Maps ensemble for semi-supervised learning of large high dimensional datasets
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
Learning visual quality inspection from multiple humans using ensembles of classifiers
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
A novel multi-view learning developed from single-view patterns
Pattern Recognition
Comparing classifiers and metaclassifiers
ICDM'11 Proceedings of the 11th international conference on Advances in data mining: applications and theoretical aspects
A multilevel information fusion approach for visual quality inspection
Information Fusion
A genetic algorithm-based rule extraction system
Applied Soft Computing
An integrated fuzzy cells-classifier
WILF'03 Proceedings of the 5th international conference on Fuzzy Logic and Applications
Ensembles based on random projections to improve the accuracy of clustering algorithms
WIRN'05 Proceedings of the 16th Italian conference on Neural Nets
Variable consistency bagging ensembles
Transactions on Rough Sets XI
Data mining in inductive databases
KDID'05 Proceedings of the 4th international conference on Knowledge Discovery in Inductive Databases
Boosting GARCH and neural networks for the prediction of heteroskedastic time series
Mathematical and Computer Modelling: An International Journal
Tri-training based on neural network ensemble algorithm
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Subsampling for efficient and effective unsupervised outlier detection ensembles
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Scalable supervised dimensionality reduction using clustering
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
Automatic text classification to support systematic reviews in medicine
Expert Systems with Applications: An International Journal
Ensembles for unsupervised outlier detection: challenges and research questions a position paper
ACM SIGKDD Explorations Newsletter
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Ensembles of learning machines constitute one of the main current directions in machine learning research, and have been applied to a wide range of real problems. Despite of the absence of an unified theory on ensembles, there are many theoretical reasons for combining multiple learners, and an empirical evidence of the effectiveness of this approach. In this paper we present a brief overview of ensemble methods, explaining the main reasons why they are able to outperform any single classifier within the ensemble, and proposing a taxonomy based on the main ways base classifiers can be generated or combined together.