An Optimized Neural Network Classification Method Based on Kernel Holistic Learning and Division

Figure 8

Sample generation of the original training set under the CC dataset and the comparison of the classification results on the test set. (a) Learning the original training set to generate the subkernel. (b) Further learning and screening to generate new sample vectors. (c) Classification results obtained by using the original training set to learn the classifier parameters. (d) Classifying the original training set with the newly generated training set and then learning the classifier parameters.

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