Proportional Learning Vector Quantization

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概要

• 論文の詳細を見る

• A proportional learning vector quantization (PLVQ) algorithm has been developed. The algorithm employs a fuzzy learning law to solve the normalization and initialization problems that are encountered in traditional learning vector quantization (LVQ). The performance of the new algorithm has been compared to that of the learning vector quantization (LVQ) and generalized learning vector quantization (GLVQ) methods by two special examples. The results show that the presented method does not only avoid the initialization problem but also solve the normalization problem.

• 日本知能情報ファジィ学会の論文
• 1998-12-15

著者

• Li Rui-ping

  Dept. Of Radiation Oncology University Of Rochester Medical Center

• Mukaidono Masao

  明治大学

関連論文

• Proportional Learning Vector Quantization

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