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What is positive-unlabeled (PU) learning, and when do you need it?

Many real problems give you confirmed positives but never confirmed negatives, only unlabeled data. The shortcut everyone reaches for quietly biases the model. The signal is naming the regime and its fix. Here is the answer.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

Many real problems give you confirmed positives but never confirmed negatives, only unlabeled data. The shortcut everyone reaches for quietly biases the model. The signal is naming the regime and its fix. Here is the answer.

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