Enrique Pelayo

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This paper presents a new algorithm, Magnitude Sensitive Competitive Learning (MSCL), which has the ability of distributing the unit weights following any magnitude calculated from the unit parameters or the input data inside the Voronoi region of the unit. This controlled behavior permits to surpass other standard Competitive Learning algorithms that only(More)
A new method, Self-Organizing Visual Assessment of cluster Tendency (SO-VAT), is given for visually assessing the cluster tendency in large data sets. It is based on training a SOM with the input samples, and then calculating the VAT image from a selected group of the generated neurons, selection that is done according to a certain density of activation.(More)
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