Modeling Basics
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Definition
Section titled “Definition”Foundational concepts for building interpretable models to support growth decisions.
Schema / Parameters
Section titled “Schema / Parameters”- Target definition, feature set, validation strategy, backtesting windows.
- Metrics: RMSE/MAE for regression; AUC/PR for classification.
- Governance: versioning, drift monitoring, and retraining policy.
Defaults
Section titled “Defaults”- Simpler, interpretable models first; document assumptions.
- Hold-out validation and periodic backtesting.
Examples
Section titled “Examples”- Lead scoring, churn prediction, LTV estimation, demand forecasting.
Limits
Section titled “Limits”- Avoid using models where rule-based logic suffices; ensure fairness and privacy.