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- W981360081 abstract "A new approach is proposed to visualize online the training of learning vector quantization algorithms. The prototypes and data samples associated to each receptive field are projected onto a two-dimensional map by using a non-linear transformation of the input space. The mapping finds a set of projection vectors by minimizing a cost function, which preserves the local topology of the input space. The proposed visualization is tested on two datasets: image segmentation and pipeline. The usefulness of the method is demonstrated by studying the behavior of Generalized LVQ, Supervised Neural Gas and Harmonic to Minimum LVQ algorithms on high-dimensional datasets." @default.
- W981360081 created "2016-06-24" @default.
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- W981360081 date "2013-01-01" @default.
- W981360081 modified "2023-09-26" @default.
- W981360081 title "Online Visualization of Prototypes and Receptive Fields Produced by LVQ Algorithms" @default.
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- W981360081 doi "https://doi.org/10.1007/978-3-642-35230-0_18" @default.
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