N. Jankowski and M. Grochowski (Poland)
Learning vector quantization (LVQ), instance selection al gorithm, prototype selection algorithm, prototype based learning, similarity based models.
This paper can be seen from two sides. From the first side as the answer of the question: how to initialize the Learning Vectors Quantization algorithm. And from sec ond side it can be seen as the method of improving of in stances selection algorithms. In the article we propose to use a conjunction of the LVQ and some of instances selec tion algorithms because it simplify the LVQ initialization and provide to better prototypes set. Moreover prepared experiments clearly show that such combinations of meth ods provide to higher classification accuracy on the unseen data. The results were computed and averaged for several benchmarks.
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