Automated Feature Engineering - Interactive Visualization

Automated feature engineering enumerates and applies all valid transformations to raw features, dramatically expanding the feature space without manual domain knowledge. Numeric features get log transforms, z-scores, and bucketing. Datetime features yield day-of-week, hour-of-day, is-weekend, and month. Categorical features get target encoding and frequency encoding. Interaction features multiply or cross two existing features. Tools like Featuretools, OpenFE, and tsfresh implement this at scale, then a selection step prunes features with low predictive gain.

• See 5 raw features (age, income, timestamp, city, category) explode into 15+ engineered features automatically
• Toggle transformation types - datetime, numeric, categorical, and interactions - to control which feature families are generated
• Adjust interaction depth: depth 1 generates 2-way interactions (age × income), depth 2 generates 3-way (log_income × age_bucket)
• Track the accuracy improvement: each feature group contributes a measurable gain over the 71.2% baseline

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