I have a tabular dataset of financial transactions with a target binary variable 'isFraud' which indicates if the transaction is fraud or not.

I want to build a model that given some past trasactions, will output one or more transactions that are likely to be non-fraud. I thought of predicting some future transaction (=rows) based on the past, and the predictor will learn only from non-fraud transactions.

My question are the following:

  1. Is there a way to predict future rows of a tabular dataset based on existing ones?
  2. Do you find this way (of predicting non-fraud) plausible?



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