Generate more examples based on our dataset data
I asked the following question but haven't received a piece of good advice so far. Do appreciate if anyone can help me. (I don't want to do UPsampling or SMOT operator).
Is there any operator in RapidMiner to increase the number of example in the dataset? I mean an operator which generate more samples from all groups and increase the total numbers of example in my dataset. I am running a DL model on my dataset but the number of samples is not enough and cannot get more samples and have to generate and produce more samples from all groups.
Also, I do not want to balance the number of samples in classes; just increasing the size of dataset let's say threefold.