The data space was mapped to high dimension feature space with Mercer kernel function, and fuzzy kernel learning vector quantization (FKLVQ) was done on the feature space to obtain the effective and stable clustering weight vectors.

 
  • 该方法通过Mercer核,将数据空间映射到高维特征空间,并在此特征空间上进行FKLVQ学习获取数据空间有效且稳定的聚类权矢量,然后在特征空间和输出空间上仅针对各空间的数据样本和它们各自的聚类权矢量进行Sammon非线性核映射。
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