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RE: LeoThread 2024-08-31 09:20

  1. Feature selection issues:

    • Including irrelevant features that introduce noise
    • Omitting important features that significantly impact the outcome
  2. Data leakage:

    • Inadvertently including information in training that wouldn't be available in real-world predictions
  3. Concept drift:

    • Changes in the underlying patterns or relationships over time
    • Model becomes less accurate as conditions evolve
  4. Sampling bias:

    • Training data not representative of the full population or real-world scenarios