Algorithmics: theory & practice
Algorithmics: theory & practice
Machine Learning
Bias/variance decompositions for likelihood-based estimators
Neural Computation
Improved Generalization Through Explicit Optimization of Margins
Machine Learning
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models
Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models
On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality
Data Mining and Knowledge Discovery
ECML '02 Proceedings of the 13th European Conference on Machine Learning
Support Vector Machine Ensemble with Bagging
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
A Unified Bias-Variance Decomposition for Zero-One and Squared Loss
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods
The Journal of Machine Learning Research
Image Categorization by Learning and Reasoning with Regions
The Journal of Machine Learning Research
Image recognition for digital libraries
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Data Mining with Computational Intelligence (Advanced Information and Knowledge Processing)
Data Mining with Computational Intelligence (Advanced Information and Knowledge Processing)
Support Vector Machines: Theory and Applications (Studies in Fuzziness and Soft Computing)
Support Vector Machines: Theory and Applications (Studies in Fuzziness and Soft Computing)
Semantic image classification with hierarchical feature subset selection
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Google's MapReduce programming model – Revisited
Science of Computer Programming
Speed Up SVM Algorithm for Massive Classification Tasks
ADMA '08 Proceedings of the 4th international conference on Advanced Data Mining and Applications
Practical Bias Variance Decomposition
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Highly Scalable SVM Modeling with Random Granulation for Spam Sender Detection
ICMLA '08 Proceedings of the 2008 Seventh International Conference on Machine Learning and Applications
Monte Carlo theory as an explanation of bagging and boosting
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
IEEE Transactions on Information Technology in Biomedicine
Evaluating Machine Learning Techniques for Automatic Image Annotations
FSKD '09 Proceedings of the 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 07
Distributed text classification with an ensemble kernel-based learning approach
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Support vector machines ensemble based on fuzzy integral for classification
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Dynamics of variance reduction in bagging and other techniques based on randomisation
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Support Vector Machine Training for Improved Hidden Markov Modeling
IEEE Transactions on Signal Processing
Face detection using spectral histograms and SVMs
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
The MPEG-7 visual standard for content description-an overview
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Image Processing
Generalized Biased Discriminant Analysis for Content-Based Image Retrieval
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
HSim: A MapReduce simulator in enabling Cloud Computing
Future Generation Computer Systems
| Hi-index | 0.09 |
A combination of classifiers leads to a substantial reduction of classification errors in a wide range of applications. Among them, support vector machine (SVM) ensembles with bagging have shown better performance in classification than a single SVM. However, the training process of SVM ensembles is notably computationally intensive, especially when the number of replicated training datasets is large. This paper presents MRESVM, a MapReduce-based distributed SVM ensemble algorithm for scalable image annotation which re-samples the training dataset based on bootstrapping and trains an SVM on each dataset in parallel using a cluster of computers. A balanced sampling strategy for bootstrapping is introduced to increase the classification accuracy. MRESVM is evaluated in both experimental and simulation environments, and the results show that the MRESVM algorithm reduces the training time significantly while achieving a high level of accuracy in classifications.