Preventing training-data leakage in model development
Training-data leakage undermines model validity. For data scientists, this thread covers common leakage modes: temporal leakage, label leakage, preprocessing leaks, and test-set contamination. Offer concrete safeguards during feature engineering, cross-validation, and pipeline deployment to keep evaluation honest and models robust in production.
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