SCG '94 Proceedings of the tenth annual symposium on Computational geometry
Neural Networks - Special issue: automatic target recognition
The Random Subspace Method for Constructing Decision Forests
IEEE Transactions on Pattern Analysis and Machine Intelligence
Accelerating exact k-means algorithms with geometric reasoning
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Constructing Boosting Algorithms from SVMs: An Application to One-Class Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining One-Class Classifiers
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
An Overview and Comparison of Voting Methods for Pattern Recognition
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
PEBL: Web Page Classification without Negative Examples
IEEE Transactions on Knowledge and Data Engineering
Support Vector Data Description
Machine Learning
Improving fuzzy c-means clustering based on feature-weight learning
Pattern Recognition Letters
One-class document classification via Neural Networks
Neurocomputing
One-Class Novelty Detection for Seizure Analysis from Intracranial EEG
The Journal of Machine Learning Research
Large Scale Multiple Kernel Learning
The Journal of Machine Learning Research
Soft clustering using weighted one-class support vector machines
Pattern Recognition
Minimum spanning tree based one-class classifier
Neurocomputing
Boosting One-Class Support Vector Machines for Multi-Class Classification
Applied Artificial Intelligence
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
Notes on a Linguistic Description as the Basis for Automatic Image Understanding
International Journal of Applied Mathematics and Computer Science
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Outlier detection using ball descriptions with adjustable metric
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Image segmentation with a hybrid ensemble of one-class support vector machines
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
One-Class Support Vector Ensembles for Image Segmentation and Classification
Journal of Mathematical Imaging and Vision
Supervised subspace projections for constructing ensembles of classifiers
Information Sciences: an International Journal
The impact of diversity on the accuracy of evidential classifier ensembles
International Journal of Approximate Reasoning
Combining diverse one-class classifiers
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
Cluster-based one-class ensemble for classification problems in information retrieval
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Dynamic fusion method using Localized Generalization Error Model
Information Sciences: an International Journal
Canadian AI'12 Proceedings of the 25th Canadian conference on Advances in Artificial Intelligence
A competitive ensemble pruning approach based on cross-validation technique
Knowledge-Based Systems
A survey of multiple classifier systems as hybrid systems
Information Fusion
Diversity measures for one-class classifier ensembles
Neurocomputing
| Hi-index | 0.07 |
This paper presents a novel multi-class classifier based on weighted one-class support vector machines (OCSVM) operating in the clustered feature space. We show that splitting the target class into atomic subsets and using these as input for one-class classifiers leads to an efficient and stable recognition algorithm. The proposed system extends our previous works on combining OCSVM classifiers to solve both one-class and multi-class classification tasks. The main contribution of this work is the novel architecture for class decomposition and combination of classifier outputs. Based on the results of a large number of computational experiments we show that the proposed method outperforms both the OCSVM for a single class, as well as the multi-class SVM for multi-class classification problems. Other advantages are the highly parallel structure of the proposed solution, which facilitates parallel training and execution stages, and the relatively small number of control parameters.