Implementing a Neural Network
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I am trying to create a linear neural network that takes in 11 inputs and gives out 5 outputs.
I've been using the following documentation as reference: https://www.mathworks.com/help/deeplearning/ug/linear-neural-networks.html
Now, x is a 75 by 11 array, of inputs for the training data.
Meanwhile, y is a 5 by 75 array, of true label outputs for the training data.
So far I have tried:
P = x'
T = y
net = linearlayer;
net = configure(net,P,T);
net.IW{11,5}
net.b{1}
I am getting an error when initializing the weights, what am I doing wrong? Since there is going to be 10 inputs, I assume that there will be 11 weights. Then there should be 1 bias weight.
Overall structure is supposed to be 11 inputs for the input layer, 1 hidden layer, and an output layer of 5 outputs. (Hence, y has 5 rows. Also, hence why x has 11 columns)
I am only trying to set up the linear neural network, not at the point of training it.
采纳的回答
x = rand(75,11);
y = randi(5, 5, 75);
P = x';
T = y;
net = linearlayer;
net = configure(net,P,T);
net.IW
net.IW{1}(5,11)
net.b{1}
2 个评论
Tony Stark
2022-10-26
Walter Roberson
2022-10-26
There are 11 scalar weights for each of the 5 outputs, a 5 x 11 array. Asking to look at the 11, 5 configuration is asking to look at the initialization weight for the last step for the last output, a scalar.
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