Adaptive Relevance Matrices in Learning Vector Quantization
نویسندگان
چکیده
منابع مشابه
Adaptive Relevance Matrices in Learning Vector Quantization
We propose a new matrix learning scheme to extend relevance learning vector quantization (RLVQ), an efficient prototype-based classification algorithm, toward a general adaptive metric. By introducing a full matrix of relevance factors in the distance measure, correlations between different features and their importance for the classification scheme can be taken into account and automated, and ...
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2009
ISSN: 0899-7667,1530-888X
DOI: 10.1162/neco.2009.11-08-908