The Essential Role of Baseline Models in Machine Learning

Don’t Skip Baseline Models in Regression.

Data scientists often jump to complex models like XGBoost without checking prediction quality. MSE scores are common, but without a baseline, it’s hard to judge their effectiveness.

Start with baseline models before diving into complexity:

• Mean Regressor: Predicts the average value of your target variable, giving you a basic reference point.

• Linear Regression: Simple, interpretable, and often a solid benchmark.

If your advanced model doesn’t significantly outperform these, you’re likely overfitting or over-engineering the problem. Always compare your results to baseline models first—complexity isn’t always better.