How do we select and engineer the best features?

How It Works:

Use automated tools (like feature importance or selection algorithms) and iterative domain-expert workshops to create and test candidate features.

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Key Benefits:

• Optimized accuracy: Focus on high-impact signals.
• Faster training: Prune irrelevant features.
• Robust models: Reduce overfitting risk.

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Real-World Use Cases:

• Retail forecasting: Lag features from past sales.
• Credit risk: Ratio features like debt-to-income.