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how to compute and plot mean square error for two vectors?

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i have a dataset to classify, using perceptron learning rule . i've calculated the weight matrix but don't know how to plot MSE .
{𝑝1 = [ 1 1 ],𝑡1 = [ 0 0 ]}, {𝑝2 = [ 1 2 ],𝑡2 = [ 0 0 ]}, {𝑝3 = [ 2 −1 ],𝑡3 = [ 0 1 ]}, {𝑝4 = [ 2 0 ],𝑡4 = [ 0 1 ]}, {𝑝5 = [ −1 2 ],𝑡5 = [ 1 0 ]}, {𝑝6 = [ −2 1 ],𝑡6 = [ 1 0 ]}, {𝑝7 = [ −1 −1 ],𝑡7 = [ 1 1 ]}, {𝑝8 = [ −2 −2 ],𝑡8 = [ 1 1 ]}.
This the dataset and w=[-2 0;0 -2],bias =[-1 0]

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Accepted Answer

Gaurav Garg
Gaurav Garg on 13 Jan 2021
Hi Deepak,
You can plot MSE/Loss and accuracy for each iteration of your training/testing.
To do this, you can make a network with 'n' number of layers, train your network on it and store the loss returned per iteration in a list. Finally, you can plot this loss on y-axis and number of iterations on x-axis.
For any more information on monitoring metrics, you can look at the documentation here.

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DEEPAK Chekuri
DEEPAK Chekuri on 13 Jan 2021
Thankyou Gaurav,
Storing mse in a new list for every iteration worked out for me and i'm instruucted to use single layer.
I've stored MSE of each iteration in new list and plotted the same.

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