Could you tell me how to use source domain data for training?

[HeYuwei]

Hello，I directly use the demo to train the model:

model = train(full(Yref),sparse(St(:,1:size(Xref,1))'),sprintf('-s 0 -c %f -q 1',100)); [~,acc,~] = predict(full(Yt),sparse(St(:,size(Xref,1)+1:end)'),model); fprintf('accuracy=%0.4f \n\n',acc); The accuracy is: start training, random runs 2 Accuracy = 20.7547% (55/265) I change liblinear to libsvm and the accuracy is: start training, random runs 3 svm accuracy=34.3396

However, when I want to utilize source domain data Ss to improve the performance: model = train(full(Yref),sparse(St(:,1:size(Xref,1))'),sprintf('-s 0 -c %f -q 1',100)); model = train([full(Ys);full(Yref)],sparse([Ss';St(:,1:size(Xref,1))']),sprintf('-s 0 -c %f -q 1',100)); fprintf('accuracy=%0.4f \n\n',acc); The accuracy is: Accuracy = 7.92453% (21/265) for libsvm, the accuracy is: accuracy=15.0943

As the demo does not show how to use source domain data for training, I cannot obtain the experimental results in the paper. Could you tell me how to use the Data Ss for training? Thank you very much.

[LilyQahh0208]

Hello, when I run the code, an error occurs. "Incorrect use of pca, The value of X must not be sparse". Could you please tell me how to solve it? Thank you very much.