K nearest neighbor classifier (K-NN) is widely discussed and applied in pattern recognition and machine learning, however, as a similar lazy classifier using local information for...
— This paper proposes two hierarchical schemes for learning, one for clustering and the other for classification problems. Both schemes can be implemented on a fuzzy lattice neu...
: In the paper nine different approaches to missing attribute values are presented and compared. Ten input data files were used to investigate the performance of the nine methods t...
Our simple fuzzy neural network first thins the set of exemplar input feature vectors and then centers a Gaussian function on each remaining one and saves its associated output la...
This paper presents an unsupervised fuzzy-kernel learning vector quantization algorithm called FKLVQ. FKLVQ is a batch type of clustering learning network by fusing the batch learn...