Complexity and multithreaded implementation analysis of one class-classifiers fuzzy combiner

Authors:
Tomasz Wilk;Michał Woźniak
Affiliations:
Department of Systems and Computer Networks, Wroclaw University of Technology, Wrocław, Poland;Department of Systems and Computer Networks, Wroclaw University of Technology, Wrocław, Poland
Venue:
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
Year:
2011

Citing 12
Cited 2

Statistical Pattern Recognition: A Review

IEEE Transactions on Pattern Analysis and Machine Intelligence
On rule pruning using fuzzy neural networks

Fuzzy Sets and Systems
Combining One-Class Classifiers

MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Combining Pattern Classifiers: Methods and Algorithms

Combining Pattern Classifiers: Methods and Algorithms
Intrusion detection in computer networks by a modular ensemble of one-class classifiers

Information Fusion
ANFIS Controller with Fuzzy Subtractive Clustering Method to Reduce Coupling Effects in Twin Rotor MIMO System (TRMS) with Less Memory and Time Usage

ICACC '09 Proceedings of the 2009 International Conference on Advanced Computer Control
Solving multiclass learning problems via error-correcting output codes

Journal of Artificial Intelligence Research
Multi-category classification by soft-max combination of binary classifiers

MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Soft computing methods applied to combination of one-class classifiers

Neurocomputing
Design of fuzzy rule-based classifier: pruning and learning

FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Flexible neuro-fuzzy systems

IEEE Transactions on Neural Networks
New results on error correcting output codes of kernel machines

IEEE Transactions on Neural Networks

Performance evaluation of hybrid implementation of support vector machine

IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
A survey of multiple classifier systems as hybrid systems

Information Fusion

Quantified Score

Hi-index	0.00

Visualization

Abstract

More recently, neural network techniques and fuzzy logic inference systems have been receiving an increasing attention. At the same time, methods of establishing decision by a group of classifiers are regarded as a general problem in various application areas of pattern recognition. Similarly to standard two-class pattern recognition methods, one-class classifiers hardly ever fit the data distribution perfectly. The paper presents fuzzy models for one-class classifier combination, compares their computational and expected space complexity with the one from ECOC and decision templates, presents possibility to speed up a fuser processing by means of multithreading.