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What test can indicate whether synthesized data is not representative?
Question: In one to three sentences, describe a way to tell whether a set of synthesized training examples is not representative, according to the source.
Sample answer: If a learning algorithm can distinguish the synthesized examples from real, non-synthesized examples—for instance because they all trace back to a narrow source like 20 car designs or 1 hour of noise—the synthesized data is likely not representative.
Key points:
- The test is whether an algorithm can distinguish synthesized from real examples.
- Distinguishability often stems from a narrow underlying source of synthesis.
- Source examples include 20 car designs and 1 hour of car noise.
Rubric: Full credit: references the distinguishability test and cites at least one example from the source. Partial credit: mentions representativeness generally without the distinguishability criterion.
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