C4.5: programs for machine learning
C4.5: programs for machine learning
The nature of statistical learning theory
The nature of statistical learning theory
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A new approximate maximal margin classification algorithm
The Journal of Machine Learning Research
Towards Incremental Fuzzy Classifiers
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Fuzzy Control: Fundamentals, Stability and Design of Fuzzy Controllers (Studies in Fuzziness and Soft Computing)
Online Passive-Aggressive Algorithms
The Journal of Machine Learning Research
Incremental Support Vector Learning: Analysis, Implementation and Applications
The Journal of Machine Learning Research
Extraction of fuzzy rules from support vector machines
Fuzzy Sets and Systems
Moving towards efficient decision tree construction
Information Sciences: an International Journal
Feature selection for multi-label naive Bayes classification
Information Sciences: an International Journal
Data-driven fuzzy modeling for Takagi-Sugeno-Kang fuzzy system
Information Sciences: an International Journal
Information Sciences: an International Journal
Fuzzy SVM for noisy data: a robust membership calculation method
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Bounded Kernel-Based Online Learning
The Journal of Machine Learning Research
On-line evolving image classifiers and their application to surface inspection
Image and Vision Computing
FSVM-CIL: fuzzy support vector machines for class imbalance learning
IEEE Transactions on Fuzzy Systems - Special section on computing with words
Fuzzy rule classifier: Capability for generalization in wood color recognition
Engineering Applications of Artificial Intelligence
So near and yet so far: New insight into properties of some well-known classifier paradigms
Information Sciences: an International Journal
A dynamic classifier ensemble selection approach for noise data
Information Sciences: an International Journal
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Design of fuzzy rule-based classifiers with semantic cointension
Information Sciences: an International Journal
An online framework for learning novel concepts over multiple cues
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Robust support vector machine with bullet hole image classification
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A new fuzzy support vector machine to evaluate credit risk
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
A parsimony fuzzy rule-based classifier using axiomatic fuzzy set theory and support vector machines
Information Sciences: an International Journal
Support vector machines for histogram-based image classification
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Incorporating visualisation quality measures to curvilinear component analysis
Information Sciences: an International Journal
Fuzzy regularized generalized eigenvalue classifier with a novel membership function
Information Sciences: an International Journal
Information Sciences: an International Journal
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Fuzzy weighting, which is designed to reduce the effects of outliers for batch classification problems, might generate unreasonable membership grades especially for the samples following an input outlier, when incorporated into online classification algorithms directly. In this paper, a generalized framework for online fuzzy weighting is presented, which incrementally calculates the membership of each incoming sample by taking into account the membership grades of previous samples in a pairwise manner. The advocated pairwise-distance based scheme can not only identify possible outliers, but also show good adaptation to the sequentially received samples in the online setting. We apply it to online Passive-Aggressive (PA) algorithm in a direct way. The resulting Fuzzy Passive-Aggressive (FPA) algorithm achieves comparable classification accuracy with benchmark incremental SVM, while still enjoying the time efficiency of simple PA, which is a Perceptron-like algorithm. Besides, FPA exhibits the best performance among PA family, which makes it a robust and efficient alternative to PA, in order to deal with unavoidable outliers in large-scale or high-dimensional real datasets. The study is supported by a series of experiments with IDA benchmark repository, as well as two real-world problems namely place recognition and radar emitter recognition.