I'm using a data set of 32 face persons and a svm-rbf to classify and a random group of 70% for train and 30% for test.
The problem is that my results are heavily dependent of the random group used for train the svm. Depending of random group sometimes I have 100% true positive rate whit 10% false positive rate, and whit another group I have 60% tpr and 30% fpr. On average the best performance is 70% tpr and 20% fpr.
What can I say about my data?
What can I do to improve my results?
(pca, lda and pca+lda don't improve the results) (I'm trying clustering now)