baseline-comparison-review

Baseline Comparison Review

Machine learning models add massive technical debt. You must constantly justify their existence by comparing them to a "dumb" baseline.

Review Protocol

1. Define the Naive Baseline:
   • For classification: Predict the majority class.
   • For regression: Predict the mean or median of the training target.
   • For time series: Predict the last known value (naive persistence).
2. Define the Heuristic Baseline: What simple if/else rule would a domain expert write?
3. Evaluate the Delta: If the complex Deep Learning model only beats the heuristic baseline by 1%, recommend keeping the heuristic. The complexity is not worth the maintenance cost.
4. Action: Always demand a baseline evaluation script before approving a new model architecture.