Adding batch normalization and a uniform-firing regularizer to mini-batch training improves TSK fuzzy classification accuracy on 12 UCI datasets, though the combined gain over the regularizer alone is not statistically significant.
Genetic learning and performance eva luation of interval type-2 fuzzy logic controllers,
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Optimize TSK Fuzzy Systems for Classification Problems: Mini-Batch Gradient Descent with Uniform Regularization and Batch Normalization
Adding batch normalization and a uniform-firing regularizer to mini-batch training improves TSK fuzzy classification accuracy on 12 UCI datasets, though the combined gain over the regularizer alone is not statistically significant.