finding accuracy

I have 4026 in lymphoma dataset plz tell how to use classifier to find the testing accuracy as

We have to fed each of the 4,026 genes in the lymphoma data set into our FNN. That is, we first used only a single gene that is ranked 1 as the input to the network. We trained the network with the training data set and, subsequently, tested the network with the test data set.The best 5-fold CV accuracy was 90.32 percent and the best testing accuracy was 80.65 percent.

plz tell how to process have struck here for more than 4 months

Answer 1

[Barry Greene]

Surely if you have used cross-validation to obtain a classification accuracy measure then you have already solved your problem? i.e. train model on 90% of data test on remaining 10% repat on each 90% then shuffle and repeat again (10 folds, 10 shuffles).