> ML_ALGORITHM // LINEAR-REGRESSION_v1.0
Ordinary Least Squares Linear Regression
The foundational parametric method for modeling continuous target variables via linear combinations of independent predictors.
Linear & Generalized Modelsclassical-supervisedhigh-intrinsicsmall (<1k)
Back to All AlgorithmsComputational Complexity
Training Complexity:O(n * p^2 + p^3) for exact solution
Inference Complexity:O(p) dot product
Hardware Profile
CPU Friendly:Yes
Requires GPU:No
Memory Footprint:low
Interpretability & Data
Interpretability Tier:high-intrinsic
Training Data Needs:small (<1k)
Interpretability Assessment
Directly readable regression coefficients represent marginal impact per unit change.
Suitable Tasks & Supported Modalities
Suitable Tasks:
regressionforecasting
Supported Modalities:
tabulartime-series
Implementing Libraries
Foundational Literature
Nouvelles méthodes pour la détermination des orbites des comètes (Method of Least Squares)Adrien-Marie Legendre (1805) · F. Didot, Paris
Theoria Motus Corporum Coelestium in Sectionibus Conicis Solem AmbientiumCarl Friedrich Gauss (1809) · Perthes et Besser, Hamburg
Common Pitfalls & Warnings
- Extrapolating beyond training feature ranges
- Ignoring leverage points and influential outliers