I used Decisiton Tree Classifier which I trained with 50 000 samples. I have also set with unlabeled samples, so I decided to use self training algorithm. Unlabeled set has 10 000 samples. I would like to ask if it is normal, that after retrainig model with these 10 000 unlabeled samples, accuracy didn't chaned as well as confusion matrix has same values? I expected some changes (better or worse prediction). Thank you in advance.