How to Classify New Dataset using Two trained models
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I have trained two models on a dataset
I want to Classify new data using the both the trained model. But Classify take one trained network. How can i do that?
Resnet50.mat
Resnet18.mat
rxTestPred = classify(resnet.trainedNet,rxTestFrames);
testAccuracy = mean(rxTestPred == rxTestLabels);
disp("Test accuracy: " + testAccuracy*100 + "%")
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KSSV
2022년 1월 28일
Question is not clear. What problem you have in using the trained model ofr new data?
답변 (1개)
yanqi liu
2022년 2월 8일
yes,sir,may be use different load variable,such as
net1 = load('Resnet50.mat')
net2 = load('Resnet18.mat')
rxTestPred = classify(net1.resnet.trainedNet,rxTestFrames);
testAccuracy = mean(rxTestPred == rxTestLabels);
disp("Resnet50 Test accuracy: " + testAccuracy*100 + "%")
rxTestPred = classify(net2.resnet.trainedNet,rxTestFrames);
testAccuracy = mean(rxTestPred == rxTestLabels);
disp("Resnet18 Test accuracy: " + testAccuracy*100 + "%")
댓글 수: 3
Nagwa megahed
2022년 6월 2일
please i ask if you reach to how implement ensemble learning in matlab ?? as i need to perform ensemble learning between more than three different networks
David Willingham
2022년 6월 3일
See this page for information on how to work with multi-input multi-output networks in MATLAB: Multiple-Input and Multiple-Output Networks
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