Linear and probabilistic models · MLD-0654
Linear regression
Predicting a numeric target as a weighted sum of features, commonly fitted by squared error.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
Estimate house prices from area and age.
Original caveat
Linearity is in parameters; transformed features can still be nonlinear in inputs.
Context and aliases
Level: Intermediate. Stages: Training · Inference.
Tags: ML.
Aliases: Ordinary least squares · OLS.
Related concepts
Concepts linking here
Original references
- scikit-learn: Gaussian processes ↗ · Reference link
- scikit-learn: linear models ↗ · Reference link
- scikit-learn: naive Bayes ↗ · Reference link
- Original reference URL ↗