how to design custom ANN using Deep Network designer app MATLAB
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Hello Everyone, I Hope you are doing well.
I want to create a simple ANN using Deep network Designer app or using code.
ANN contain input layer, 10 neurons in hidden layer with sigmoid activation and output layer with classifciaton and softmax layer
I have the dataset of shape 250x1000. I have attached the dataset below. which contain label as well.
I also want to be label in catogorical form . Like 1 name as 'Class1'
How can i do it in MATLAB
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yanqi liu
le 1 Mar 2022
clc; clear all; close all;
load Datasetn
layers = [
imageInputLayer([1000 1 1])
fullyConnectedLayer(10)
reluLayer
fullyConnectedLayer(5)
softmaxLayer
classificationLayer];
opts = trainingOptions('adam', ...
'MaxEpochs',200, ...
'Shuffle','every-epoch', ...
'Plots','training-progress', ...
'Verbose',false, ...
'ExecutionEnvironment', 'cpu', ...
'ValidationPatience',Inf);
xc = reshape(dataset', [1000,1,1,250]);
% 'Class1'
yc = [];
for i = 1 : length(label)
yc{i,1} = ['Class' num2str(double(label(i)))];
end
yc = categorical(yc);
disp(yc)
net = trainNetwork(xc,yc,layers,opts);
2 commentaires
yanqi liu
le 1 Mar 2022
yes,sir
clc; clear all; close all;
load Datasetn
idx = randperm(length(label)) ;
dataset = dataset(idx,:);
label = label(idx,:);
m = round(length(label)*0.8) ;
dataset1 = dataset(1:m,:); label1 = label(1:m,:);
dataset2 = dataset(1+m:end,:); label2 = label(1+m:end,:);
layers = [
imageInputLayer([1000 1 1])
fullyConnectedLayer(10)
reluLayer
fullyConnectedLayer(5)
softmaxLayer
classificationLayer];
opts = trainingOptions('adam', ...
'MaxEpochs',200, ...
'Shuffle','every-epoch', ...
'Plots','training-progress', ...
'Verbose',false, ...
'ExecutionEnvironment', 'cpu', ...
'ValidationPatience',Inf);
xc = reshape(dataset1', [1000,1,1,m]);
% 'Class1'
yc = [];
for i = 1 : length(label1)
yc{i,1} = ['Class' num2str(double(label1(i)))];
end
yc = categorical(yc);
disp(yc)
net = trainNetwork(xc,yc,layers,opts);
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