In this paper we present a necessary and sufficient condition for global optimality of unsupervised Learning Vector Quantization (LVQ) in kernel space. In particular, we generalize the results presented for expansive and competitive learning for vector quantization in Euclidean space, to the general
Expansive and Competitive Learning for Vector Quantization
✍ Scribed by J. Muñoz-Perez; J. A. Gomez-Ruiz; E. Lopez-Rubio; M. A. Garcia-Bernal
- Book ID
- 110341100
- Publisher
- Springer US
- Year
- 2002
- Tongue
- English
- Weight
- 273 KB
- Volume
- 15
- Category
- Article
- ISSN
- 1370-4621
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