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How to determine the number of neurons in a neural network?
I want to write a neural network for detecting network anomalies. Feedforward neural network. The data represents 12 parameters inherent in incoming packets. Those. does this mean I should have 12 input neurons, 12 neurons in the hidden layer, and 2 neurons in the output?
In this case, each neuron in the input layer will receive one parameter from the packet?
Am I understanding everything correctly or should I do it differently?
I don’t know anything about this topic yet, and I haven’t found a specific practical answer yet either in the literature or on the forums. Tell me please.
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It is better not to try to solve this problem as a classification, but immediately take up approaches from anomaly detection.
There is no formula for determining the size of hidden layers. Often it is determined by enumeration or based on common sense.
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