Algorithms for clustering data
Algorithms for clustering data
Decision Combination in Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical mixtures of experts and the EM algorithm
Neural Computation
Improving regression estimation: Averaging methods for variance reduction with extensions to general convex measure optimization
Combination of Multiple Classifiers Using Local Accuracy Estimates
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning to learn
Classification by pairwise coupling
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Effective supra-classifiers for knowledge base construction
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
Advances in Distributed and Parallel Knowledge Discovery
Advances in Distributed and Parallel Knowledge Discovery
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ensemble Methods in Machine Learning
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Collective, Hierarchical Clustering from Distributed, Heterogeneous Data
Revised Papers from Large-Scale Parallel Data Mining, Workshop on Large-Scale Parallel KDD Systems, SIGKDD
A Hierarchical Multiclassifier System for Hyperspectral Data Analysis
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
The VLDB Journal — The International Journal on Very Large Data Bases
Cluster ensembles: a knowledge reuse framework for combining partitionings
Eighteenth national conference on Artificial intelligence
Data Clustering Using Evidence Accumulation
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Linear and order statistics combiners for reliable pattern classification
Linear and order statistics combiners for reliable pattern classification
Modular learning through output space decomposition
Modular learning through output space decomposition
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
Neural and statistical classifiers-taxonomy and two case studies
IEEE Transactions on Neural Networks
Structurally adaptive modular networks for nonstationary environments
IEEE Transactions on Neural Networks
Efficient classification for multiclass problems using modular neural networks
IEEE Transactions on Neural Networks
Experts' Boasting in Trainable Fusion Rules
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cluster ensembles --- a knowledge reuse framework for combining multiple partitions
The Journal of Machine Learning Research
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Maximum likelihood combination of multiple clusterings
Pattern Recognition Letters
Evaluation of Stability of k-Means Cluster Ensembles with Respect to Random Initialization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Moderate diversity for better cluster ensembles
Information Fusion
On solving the face recognition problem with one training sample per subject
Pattern Recognition
Trainable fusion rules. I. Large sample size case
Neural Networks
Computational Biology and Chemistry
Intelligent Data Analysis
Cumulative Voting Consensus Method for Partitions with Variable Number of Clusters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using neural network ensembles for bankruptcy prediction and credit scoring
Expert Systems with Applications: An International Journal
CONSENSUS-BASED ENSEMBLES OF SOFT CLUSTERINGS
Applied Artificial Intelligence
An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring
Expert Systems with Applications: An International Journal
Diversity in Combinations of Heterogeneous Classifiers
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Field independent probabilistic model for clustering multi-field documents
Information Processing and Management: an International Journal
Selecting diversifying heuristics for cluster ensembles
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Reducing the overconfidence of base classifiers when combining their decisions
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Finding natural clusters using multi-clusterer combiner based on shared nearest neighbors
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Application of a fuzzy integral for weak classifiers boosting
Pattern Recognition and Image Analysis
Ensemble of classifiers based on hard instances
MCPR'11 Proceedings of the Third Mexican conference on Pattern recognition
Dynamic classifier ensemble model for customer classification with imbalanced class distribution
Expert Systems with Applications: An International Journal
Combining classifiers with particle swarms
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Self-organizing map initialization
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Joint cluster based co-clustering for clustering ensembles
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Semi-supervised multiple classifier systems: background and research directions
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Diversity measure for multiple classifier systems
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
On ECOC as binary ensemble classifiers
MLDM'05 Proceedings of the 4th international conference on Machine Learning and Data Mining in Pattern Recognition
Relationship between diversity and correlation in multi-classifier systems
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Human face analysis: from identity to emotion and intention recognition
ICEB'10 Proceedings of the Third international conference on Ethics and Policy of Biometrics and International Data Sharing
Improving bagging performance through multi-algorithm ensembles
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Software effort models should be assessed via leave-one-out validation
Journal of Systems and Software
Ensemble canonical correlation analysis
Applied Intelligence
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While a variety of multiple classifier systems have been studied since at least the late 1950's, this area came alive in the 90's with significant theoretical advances as well as numerous successful practical applications. This article argues that our current understanding of ensemble-type multiclassifier systems is now quite mature and exhorts the reader to consider a broader set of models and situations for further progress. Some of these scenarios have already been considered in classical pattern recognition literature, but revisiting them often leads to new insights and progress. As an example, we consider how to integrate multiple clusterings, a problem central to several emerging distributed data mining applications. We also revisit output space decomposition to show how this can lead to extraction of valuable domain knowledge in addition to improved classification accuracy.