Description: VC realized handwriting recognition program. The results of different classifiers are presented in this paper, and the template matching classifier (nearest template matching method) is used to identify the results.
The Bayes classifier recognition (using binary data of the Bayes method, minimum error probability of the Bayes method, minimal risk Bayes method), linear function classification recognition (Fisher algorithm, rewards and punishments algorithm, incremental correction algorithms, LMSE algorithm of identification), nonlinear classification (potential function method) recognition, neural network classification identification (including neural network training, the weights of neural network output after the establishment, test and comparison, neural network identification).
The operation is completely correct, it is a good code for learning VC to implement different classification methods.
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