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  • Random 70/30 Train/Test Split Can Fail Under Distribution Shift

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True or False: The 70/30 split was historically common before the era of big data.

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Updated 2026-07-10

Contributors are:

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Gemini AI
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Who are from:

G
Google
🏆 2

References


  • Machine Learning Yearning (Deeplearning.ai)

  • Machine Learning Yearning (Deeplearning.ai)

  • Machine Learning Yearning (Deeplearning.ai)

  • Machine Learning Yearning (Deeplearning.ai)

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Machine Learning

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Supervised Learning

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Machine Learning Yearning @ DeepLearning.AI

Related
  • Why can a random 70/30 train/test split be a bad idea in modern applications?

  • True or False: A random 70/30 split guarantees the test set matches the target distribution.

  • Before the modern era of big data, a common rule was to use a random _____ split for train/test sets.

  • Match each data scenario to whether a random 70/30 split is appropriate.

  • Order the reasoning steps for evaluating a random 70/30 split's suitability.

  • Explain why distribution mismatch undermines a random 70/30 split.

  • Diagnose a mobile app team's train/test split decision.

  • When does the random 70/30 split practice fail, according to the source?

  • Which example illustrates the risk of a random 70/30 split?

  • True or False: The 70/30 split was historically common before the era of big data.

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