Neural Mapminmax option for a set
조회 수: 1 (최근 30일)
이전 댓글 표시
When I use mapminmax like,
net.inputs{1}.processFcns = {'removeconstantrows','mapminmax'};
net.outputs{2}.processFcns = {'removeconstantrows','mapminmax'};
it will mapminmax the whole set of:
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;
???
Or it would individually mapminmax values of valRatio and TestRatio based on the trainRatio minmax procedure ?
If its a common normalization, would´t the testset or the valset mess with the normalization of the trainset ? Andre
댓글 수: 0
채택된 답변
Greg Heath
2014년 6월 6일
If the total data set is assumed to be a random sample from the population and the trn/val/tst subsets are random samples from the total, then the expectation is that there is no way to tell that the val and tst subsets are not random samples from the population.
However, this is statistics. Therefore there is no guaranty.
As a result, it is not unwise to be aware of the summary statistics of those sets of data and any new data.
Hope this helps.
Greg
댓글 수: 1
Greg Heath
2014년 6월 6일
The training record tr in [ net tr ] = train(net,x,t) contains the indices of the separate trn/val/tst subsets. You can always check to see if renormalizing the 3 subsets separately significantly affects the 3 error rates.
추가 답변 (0개)
참고 항목
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!