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Weight Updates Calculated

Weight Updates Calculated

Understand the weight update method in a neural network with the help of a numerical example.

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An example of calculating a weight update

The following network is one we’ve worked with before, but this time we’ve added example output values from the first hidden node oj=1o_{j=1} and the second hidden node oj=2o_{j=2}. These are just made-up numbers to illustrate the method and aren’t properly worked out by feeding signals forward from the input layer.

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Update weights to reduce error in neural network
Update weights to reduce error in neural network

We want to update the weight w11w_{11} between the hidden and output layers, which currently has the value 2.02.0.

Let’s write out the error slope again:

Ewjk=(tkok)sigmoid(jwjkoj)(1sigmoid(jwjkoj))oj\frac{\partial E}{\partial w_{jk}} = -(t_k - o_k)\cdot \text{sigmoid}\left(\sum_j w_{jk} \cdot o_j \right) \left(1-\text{sigmoid}\left(\sum_j w_{jk} \cdot o_j\right)\right)\cdot o_j ...