domains / families / data / ml-data-leakage-guard

ml-data-leakage-guard

separate

Detects and prevents data leakage in machine learning and mathematical modeling. Use after ML tasks involving data cleaning, feature engineering, data augmentation, algorithm development, normalization, missing value imputation, dimensionality reduction, feature selection, or time series modeling. Checks if features/statistics would be available at prediction time.

When to use

• Data preprocessing (normalization, standardization, scaling)
• Missing value imputation
• Feature engineering and feature selection
• Dimensionality reduction (PCA, SVD, t-SNE)
• Target encoding or label encoding
• Time series feature construction
• Data augmentation strategies
• Algorithm development and optimization

When not to use

• pure theoretical ML discussions
• model architecture design without data preprocessing
• hyperparameter tuning without data-dependent operations

Skill page

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