Least Squares Method
Version 1.0.0 · Updated 2026-07-30
CORE DEFINITION
A mathematical method that finds the best-fitting model parameters by minimizing the sum of squares of the differences between predicted values and actual values. It is the foundation of statistical models such as linear regression. Scaffolding role: It gives a mathematical definition to "best fit." Intuitively, one knows to find the most suitable line; the least squares method provides a precise optimization objective, making the fitting process computable.
SCAFFOLDING EFFECT
Reduce cognitive load
Gives a mathematical definition to "best fit." Intuitively, one knows to find the most suitable line; the least squares method provides a precise optimization objective, making the fitting process computable.
Anchor fast decisions
Parameter estimation method: choose the parameters that minimize the sum of squares of the differences between observed values and model predictions. The mechanism is minimization of squared loss, which is robust to noise and can be solved analytically.
MINIMUM ACTION
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Source support: Explicit
- zh.wikipedia.orghttps://zh.wikipedia.org/wiki/%E6%9C%80%E5%B0%8F%E4%BA%8C%E4%B9%98%E6%B3%95verified
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