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A Nearest Features Classifier Using a Self-organizing Map for Memory Base Evaluation
[chapter]
2006
Lecture Notes in Computer Science
Memory base learning is one of main fields in the area of machine learning. We propose a new methodology for addressing the classification task that relies on the main idea of the k -nearest neighbors algorithm, which is the most important representative of this field. In the proposed approach, given an unclassified pattern, a set of neighboring patterns is found, but not necessarily using all input feature dimensions. Also, following the concept of the naïve Bayesian classifier, we adopt the
doi:10.1007/11840930_40
fatcat:za4p25ovdjedde4d3wswr4zum4