Leave-one-​out-crossv​alind

2 Ansichten (letzte 30 Tage)
Abu Qusay
Abu Qusay am 28 Jun. 2015
Bearbeitet: Abu Qusay am 28 Jun. 2015
After extracting HOG features of some male and female pictures, I'm trying to use the Leave-one-out-method to classify my data. Due the standard way to write it in Matlab is:
[Train, Test] = crossvalind('LeaveMOut', N, M);
What I should write instead of N and M ? Also, should I write the code inside or outside a loop? this is my code, where I have training folder for Male (80 images) and female (80 images), and testing folder with (10 random images).
for i = 1:10
[Train, Test] = crossvalind('LeaveMOut', N, 1);
SVMStruct = svmtrain(Training_Set (Train), train_label (Train));
Gender = svmclassify(SVMStruct, Test_Set_MF (Test));
end
Notes:
  • Training_Set : an array contains HOG features of training folder images.
  • Test_Set_MF : an array contains HOG features of test folder images.
  • N : total number of images in training folder.
  • SVM should detect which images are male and which are female.

Antworten (0)

Kategorien

Mehr zu Statistics and Machine Learning Toolbox finden Sie in Help Center und File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by