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task1_bgp_few.m
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task1_bgp_few.m
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clear
load('data_main.mat')
%combine data from Digital and Sagen sensors
% combine BGP features data
Train_All_Data_BGP = horzcat(Train_All_Data_DigiBGP, Train_All_Data_SageBGP)
Train_All_Data_BGP = num2cell(Train_All_Data_BGP, 1)
Train_All_Label_BGP = horzcat(Train_All_Label_DigiBGP, Train_All_Label_SageBGP)
Gen_All_Data_BGP = horzcat(Test_All_Data_DigiBGP, Test_All_Data_SageBGP)
Gen_All_Label_BGP = horzcat(Test_All_Label_DigiBGP, Test_All_Label_SageBGP)
Val_All_Data_BGP = Gen_All_Data_BGP(: , 1:2018)
Val_All_Label_BGP = Gen_All_Label_BGP(: , 1:2018)
Test_All_Data_BGP = Gen_All_Data_BGP(: , 2019:4036)
Test_All_Label_BGP = Gen_All_Label_BGP(: , 2019:4036)
rng('default')
hiddenSize1 = 50;
autoenc1 = trainAutoencoder(Train_All_Data_BGP,hiddenSize1, ...
'MaxEpochs',400, ...
'L2WeightRegularization',0.004, ...
'SparsityRegularization',4, ...
'SparsityProportion',0.15, ...
'ScaleData', false);
%view(autoenc1)
feat1 = encode(autoenc1,Train_All_Data_BGP);
softnet = trainSoftmaxLayer(feat1,Train_All_Label_BGP,'MaxEpochs',400);
%view(softnet)
deepnet = stack(autoenc1,softnet);
view(deepnet)
% plot roc and confusion
% For testing
%%y = deepnet(Test_All_Data_BGP);
%figure(1)
%plotconfusion(Test_All_Label_BGP,y);
%figure(2)
%plotroc(Test_All_Label_BGP,y)
% For training
%y = deepnet(Train_All_Data_BGP);
%figure(3)
%plotconfusion(Train_All_Label_BGP,y);
%figure(4)
%plotroc(Train_All_Label_BGP,y)
% Perform fine tuning
inputSize = 216
xTrain = zeros(inputSize,numel(Train_All_Data_BGP));
for i = 1:numel(Train_All_Data_BGP)
xTrain(:,i) = Train_All_Data_BGP{i}(:);
end
deepnet_bp = train(deepnet,xTrain,Train_All_Label_BGP);
% plot roc and confusion
% For testing
y = deepnet_bp(Test_All_Data_BGP);
figure(4)
plotconfusion(Test_All_Label_BGP,y);
%figure(6)
%plotroc(Test_All_Label_BGP,y)
ezroc3(y,Test_All_Label_BGP,2,'',1);
% For validation
y = deepnet_bp(Val_All_Data_BGP);
figure(5)
plotconfusion(Val_All_Label_BGP,y);
%figure(6)
%plotroc(Test_All_Label_BGP,y)
ezroc3(y,Val_All_Label_BGP,2,'',1);
% For training
Train_All_Data_BGP_rev = cell2mat(Train_All_Data_BGP)
y = deepnet_bp(Train_All_Data_BGP_rev);
figure(7)
plotconfusion(Train_All_Label_BGP,y);
%figure(8)
%plotroc(Train_All_Label_BGP,y)
ezroc3(y,Train_All_Label_BGP,2,'',1);
save('data_task1_bgp_few.mat')