To model the relationship between two continuous variables, simple linear regression is utilized. The goal is frequently to anticipate the value of an output variable (or responder) based on the value of an input variable (or predictor).
Linear regression is straightforward to execute and the output coefficients are easier to interpret. This algorithm is the best to employ when you know the independent and dependent variables have a linear relationship because it is less difficult than other algorithms.
Linear-regression models have become a proven way to scientifically and reliably predict the future. Because linear regression is a long-established statistical procedure, the properties of linear-regression models are well understood and can be trained very quickly.
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