Unsupervised learning of neural network classifica
2016-08-23
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As concerns cognitive ability and environmental constraints, are often impossible or very difficult to obtain the desired output, in this case, the neural network based on supervised learning is often powerless.
With supervised learning neural networks, unsupervised learning neural network without knowing the expected output in the learning process. Which is similar to real neural networks in the brain, can continue to observe, analyze and compare, automatically reveals the inherent law and essence of samples, so you can have the similar characteristics (attributes) samples for accurate classification and recognition. Is described in detail in this chapter for competitive neural networks and self organizing feature map (SOFM) neural network structure and principles and to illustrate their specific scope of applicati
With supervised learning neural networks, unsupervised learning neural network without knowing the expected output in the learning process. Which is similar to real neural networks in the brain, can continue to observe, analyze and compare, automatically reveals the inherent law and essence of samples, so you can have the similar characteristics (attributes) samples for accurate classification and recognition. Is described in detail in this chapter for competitive neural networks and self organizing feature map (SOFM) neural network structure and principles and to illustrate their specific scope of applicati
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