An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Data mining: concepts and techniques
Data mining: concepts and techniques
Machine Learning
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
AINE: An Immunological Approach to Data Mining
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm
Genetic Programming and Evolvable Machines
A new classifier based on resource limited artificial immune systems
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
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This article proposes a new classifier inspired on a biological immune systems' characteristic. This immune based predictor also belongs to the class of k-nearest-neighbors algorithms. Nevertheless, its main features, compared to other artificial immune classifiers, are the assumption that training set is the antibodies' population and a suppression mechanism that tries to reduce the training set into a smaller subset. This subset is supposed to contain the most significative samples, without loosing much capability of generalization. It is known that in prediction problems, the choice of a good training set is crucial for the classification process. And this is the focus of this research. Experiments using some benchmarks and the analysis of the results of our ongoing work are presented.