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Q:Interpreting neurons in the neural network

Q:神经网络中的神经元解释

I have come up with a solution for a classification problem using neural networks. I have got the weight vectors for the same too. The data is 5 dimensional and there are 5 neurons in the hidden layer. Suppose neuron 1 has input weights w11, w12, ...w15 I have to explain the physical interpretation of these weights...like a combination of these weights, what does it represent in the problem.Does any such interpretation exist or is that the neuron has no specific interpretation as such?

I have come up with a solution for a classification problem using neural networks. I have got the weight vectors for the same too. The data is 5 dimensional and there are 5 neurons in the hidden layer. Suppose neuron 1 has input weights w11, w12, ...w15 I have to explain the physical interpretation of these weights...like a combination of these weights, what does it represent in the problem.Does any such interpretation exist or is that the neuron has no specific interpretation as such?

answer1: 回答1:

A single neuron will not give you any interpretation, but looking at a combination of couple of neuron can tell you which pattern in your data is captured by that set of neurons (assuming your data is complicated enough to have multiple patterns and yet not too complicated that there is too many connections in the network).

一个单一的神经元不会给你任何的解释,但看着组合对神经元可以告诉你,你的数据是由模式组神经元捕获(假设你有足够多的数据是复杂的模式,却不太复杂,网络中有太多的连接)。

matlab  machine-learning  neural-network  bias-neuron