so the point of pseudo labeling is that we've got a few labeled examples which we train some sort of weak model using the few labeled examples that we've got and then we start to use the weak model to make predictions on unlabeled data that we then treat as if they would have truth if the model is confident beyond the certain point so illustration I start off with my label examples one black one white and I've got all this unlabeled data now the hope is that if the model is trained using just these two data points it will be confident