Identity Link Function
In statistics and machine learning, the identity link function is a function that relates the linear predictor of a regression model to the response variable. It is used in generalized linear models (GLMs) to model continuous response variables. The identity link function simply states that the linear predictor is equal to the response variable. This means that the expected value of the response variable is equal to the linear predictor. The identity link function is commonly used in linear regression models, where the response variable is continuous and the relationship between the response variable and the predictor variables is linear.
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