CODEWITHSUNDEEP
artificial-intelligenceneural-networkclassification
egorman44
egorman44

Reputation: 23

Noisy neural network training set

Recently I found an example where a Neural Network tried to classify characters. There were trained two neural networks. One with a noisy data set and second without it. I tried to find any theoretical explanation why using the noisy training set gives better results, but I didn't get enough to understand. Can anyone explain me? Thanks in advance

Upvotes: 2

Views: 792

Answers (1)

Denis Tarasov
Denis Tarasov

Reputation: 1051

Training NN with noise improves generalization (the ability of network to provide correct predictions for new unknown data), because noise makes more difficult for NN to fit each data point precisely (preventing NN from just memorizing exact values of training data, thus forcing it to learn more meaningful relationships). For mathematical details and information about relationship between noise and other forms of regularization, you can take a look at this paper

Upvotes: 1

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