feature-engineering-optimizer

# Feature Engineering Optimizer ## Overview Optimizes feature engineering pipelines and feature store configurations. This skill improves ML feature quality, performance, and serving efficiency. ## Capabilities - Feature importance analysis - Feature correlation detection - Encoding strategy recommendations - Feature freshness optimization - Online/offline feature sync - Feature versioning - Point-in-time correctness validation - Feature serving optimization ## Input Schema ```json { "features": [{ "name": "string", "definition": "string", "type": "string" }], "targetVariable": "string", "useCases": ["batch|realtime|streaming"], "performanceRequirements": "object" } ``` ## Output Schema ```json { "optimizedFeatures": ["object"], "removedFeatures": ["string"], "engineeringRecommendations": ["object"], "servingConfig": "object" } ``` ## Target Processes - Feature Store Setup - A/B Testing Pipeline ## Usage Guidelines 1. Provide complete feature definitions 2. Specify target variable for importance analysis 3. Define use cases (batch, realtime, streaming) 4. Include performance requirements for serving optimization ## Best Practices - Validate point-in-time correctness for training features - Remove highly correlated features to reduce redundancy - Optimize feature freshness based on actual requirements - Version features alongside model versions - Monitor feature drift in production