Learning Vector Quantization with adaptive prototype addition and removal

@article{Grbovic2009LearningVQ,
  title={Learning Vector Quantization with adaptive prototype addition and removal},
  author={Mihajlo Grbovic and Slobodan Vucetic},
  journal={2009 International Joint Conference on Neural Networks},
  year={2009},
  pages={994-1001}
}
Learning Vector Quantization (LVQ) is a popular class of nearest prototype classifiers for multiclass classification. Learning algorithms from this family are widely used because of their intuitively clear learning process and ease of implementation. They run efficiently and in many cases provide state of the art performance. In this paper we propose a modification of the LVQ algorithm that addresses problems of determining appropriate number of prototypes, sensitivity to initialization, and… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 29 references

LVQ-PAK Learning vector quantization program package

T. Kohonen, J. Kangas, J. Laaksoonen, K. Torkolla
Lab. Comput. Inform. Sci. Rakentajanaukio, Finland, Tech. Rep. 2C • 1992
View 4 Excerpts
Highly Influenced

Soft Learning Vector Quantization

Neural Computation • 2003
View 4 Excerpts
Highly Influenced

Dynamics and Generalization Ability of LVQ Algorithms

Journal of Machine Learning Research • 2007
View 1 Excerpt

Alternative learning vector quantization

Pattern Recognition • 2006
View 1 Excerpt

and Th

F.-M. Schleif, B. Hammer
Villmann. Margin based Active Learning for LVQ Networks. In Proc. of ESANN, pp. 539-545 • 2006
View 1 Excerpt

A novel kernel prototype-based learning algorithm

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. • 2004
View 1 Excerpt

Energy generalized LVQ with relevance factors

2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541) • 2004
View 1 Excerpt

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